JPH09253304A - Information processor for game place - Google Patents

Abstract

PROBLEM TO BE SOLVED: To accurately provide the business prediction information of sales and profits, etc., by respectively computing the visiting person number information of the next time and the predicted total using game value information of the entire game place of the next time, etc., computing the predicted sales information and predicted profit information of the next time from the arithmetic results and displaying them at adisplay means. SOLUTION: A game shop 1 is provided with a management device 11 and it is connected through an ATM exchange 15 to a card company 2 by a telephone line 45. Also, the game shop 1 is provided with a business analysis device 12, a repeater 13 and an island unit 16 composed by arraying many enclosed ball type game machines, etc., in addition. Then, in the business analysis device 12, after computing the visiting person number information of the next time, the predicted total using game value information of the entire game place of the next time based on the visiting person number information and the predicted total using game value information for the respective game maghines of the next time based on the game value information respectively, the sales information and the predated profit information are computed based on game machine setting information and the predicted total using game value information for the respective game machines and the result is displayed at the display means.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an information processing device in a game arcade, and more specifically, information on a game arcade that collects information of a plurality of terminal devices in the game arcade and predictively notifies management information from the collected information. Processing device (eg, business analysis device)
About.

[0002]

2. Description of the Related Art Generally, as a game arcade equipment using a game medium, for example, a pachinko game machine, an arrange ball machine, a sparrow ball machine, a throttle machine using a medal (turned-type throttle game machine), and a ball are used. There is a throttle machine (turn-type throttle game machine) and the like. Conventionally, in an average game arcade, about 300 gaming machines are arranged. When it comes to large stores, about 1000 gaming machines are located. The information processing device (eg, management analysis device, management device) collects information from these gaming machines and gaming-related equipment (eg, ball lending machine, card issuing machine, etc.) and performs arithmetic processing, for example, sales information, games Obtained huge amount of sales information such as machine operation information. Further, recently, the amount of game information collected by the information on the game arcade has increased, and the information has become complicated. Based on these information, the manager empirically adjusts the gaming machine in consideration of the target profit of the next business day.

[0003]

However, the conventional information processing apparatus has the following problems. (A) Recently, the number of information collected at a game hall has increased and the types of information have become complicated, and various processed information has been provided. However, despite providing various processed information, a conventional information processing apparatus that can effectively utilize the increased and complicated game information and provide management forecast information such as game hall sales and profits as concrete data. There was no. (B) Also, by using the information provided by the conventional information processing device, the manager considers the characteristics of the gaming machine aiming for the target profit of the next business day, etc., and adjusts the nail of the gaming machine or changes the setting probability. Etc. are carried out according to rules of thumb. In this way, from the current situation of adjusting nails and the like based on empirical rules, even if various information is provided to the manager by the conventional information processing apparatus as described above, it is possible that the manager can grasp the experience empirically. Only the information of the department was used.

(C) Even if the nail adjustment or the like is performed in accordance with the empirical rule to aim for the target profit or the like, it is impossible to know what kind of result actually comes close to without doing business.
Moreover, the result was only a sensory prediction (poor reliability). (D) Even in the current situation where various types of information are provided due to the increase in the number of information items and the complexity of information types as described above, the operation of the adjustment method of the set value of the gaming machine in order to approach the target profit of the next day business etc. An information processing device capable of simplifying the above is desired. (E) In addition, operability that allows the owner to change the information value by his / her own will to calculate the profit etc. by trial and error, in order to approach the target profit of the next day business, etc. A good information processing device is desired.

Therefore, the present invention has been made in view of the above-mentioned problems, and it is possible to effectively use the increased and complicated game information and to have good operability, and to provide management forecast information such as sales and profits. The purpose of the present invention is to provide an information processing device.

[0006]

In order to achieve the above object, an information processing device of a game hall according to the invention as set forth in claim 1 collects information of the game hall and predicts and notifies management information from the collected information. An information processing device for a venue, a predictive visitor number calculation means for predicting next visitor number information, and a prediction for calculating a predicted total used game value information of the next entire game hall based on at least the next predicted visitor number information Based on the total used game value information calculating means and at least the next predicted total used game value information of the entire game arcade, the predicted total used game value information for each next gaming machine is calculated. Means, a predicted sales / profit information calculation means for calculating the next predicted sales information and predicted profit information based on the gaming machine setting information and the predicted total used gaming value information for each of the next gaming machines, and the prediction Display means for displaying the predicted sales information or prediction profit information based on the output of the upper and profit information calculating means, and further comprising a.

An information processing device for a game arcade according to a second aspect of the present invention is an information processing device for a game arcade, which collects information about a game arcade and predictively notifies management information from the collected information. By the predicted visitor number information calculating means for calculating the next predicted visitor number from the sequential visitor number information, the total used game value information for a predetermined past, the visitor number information for a predetermined past, and the predicted visitor number information calculating means Predicted total used game value information calculating means for calculating the estimated total used game value information of the next entire game area based on the calculated predicted number of people visiting the store, total used game value information for a predetermined past, and a predetermined past Minutes based on the used game value information for each game model, the installed machine number information of the game machine, and the predicted total used game value information calculated by the predicted total used game value information calculating means, Predicted gaming machine used gaming value information calculating means for calculating measured used gaming value information, gaming machine setting information, and next predicted used game for each gaming machine calculated by the predicted gaming machine used gaming value information calculating means Predicted sales / profit information calculation means for calculating the next predicted sales information and predicted profit information based on the value information, and predicted sales information, predicted profit information or gaming machine based on the output of the predicted sales / profit information calculation means A display means for displaying any one or more pieces of information among the game machine setting values for each.

As a preferable mode, for example, as described in claim 3, the display means may display the predicted number of people visiting the store calculated by the predicted number of people visiting the store. For example, as described in claim 4, based on the business hours information, the predicted total used game value information calculated by the predicted total used game value calculation means, and the installed machine number information, the predicted gaming machine operating rate You may make it have a prediction game machine utilization rate information calculation means to calculate information, and the said display means may display the prediction game machine utilization rate information calculated by the said prediction game machine utilization rate information calculation means.

For example, according to claim 5, the forecast information change input means for inputting a change of the forecast sales information or the forecast profit information calculated by the forecast sales / profit information calculating means, and the forecast information change input means. Based on the changed predicted sales information or predicted profit information, the gaming machine setting information associated with the gaming machine is changed to calculate a value close to the changed predicted sales information or predicted profit information. It may have machine setting information variable calculation means, and the display means may display the set value of the game machine setting information calculated by the game machine setting information variable calculation means.

For example, as described in claim 6, the game machine setting information information change input means for changing and inputting the game machine setting information for changing the game machine setting information associated with the game machine is provided, and the predicted sales / Profit information calculation means, gaming machine setting information changed by the gaming machine setting information information change input means, and predicted used gaming value information for each gaming machine calculated by the predicted gaming machine used gaming value information calculating means Based on the above, the forecast sales / profit information recalculation means for newly recalculating the next forecast sales information and the forecast profit information may be provided. For example, as described in claim 7, the information processing device of the game arcade is connected to a management device for exchanging information with a terminal device such as a game machine so as to be able to transmit information, and the set game machine setting information. You may make it have an information transfer means which transfers to the said management apparatus.

[0011]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described below with reference to the drawings as an embodiment in which a management system for a card-type game system is applied. That is, in the present embodiment, the management analysis device collects various kinds of information of the gaming machine and each terminal device, performs necessary arithmetic processing, predictive notification of management information (particularly screen display), and information processing of the game hall. It is an example in which the present invention is applied to a business analysis device as a device. (I) Overall Arrangement of Game Hall Equipment FIG. 1 is a block diagram showing the overall arrangement of the game hall equipment using the management analyzer. In FIG. 1, 1 is a game shop, 2
Is a card management company (hereinafter referred to as a card company, as well as drawings). The game store 1 is roughly divided into a card management device (hereinafter referred to as a management device) 11, a management analysis device (information processing device at a game hall) 12, a repeater 13, a prize POS (prize exchange device) 14, an ATM exchange 15, Island unit (so-called island equipment: equivalent to game machine installation equipment) 16, repeater 2
1, 22, a card issuing machine (information medium issuing apparatus) 23, and an updating machine (information medium updating apparatus) 24 are arranged.

Further, the island unit 16 includes a large amount of money addition machine (value added device) 25, a plurality of gaming machines (enclosed ball type gaming machines) 31a to 31n (hereinafter simply referred to as 31), and a supply device. 32 are arranged. Although only one island unit 16 and one repeater (sub-repeater) 22 are shown in FIG.
6 and a plurality of repeaters (sub-repeaters) 22 are provided in units of islands. The prize POS 14, the card issuing machine 23, the renewal machine 24, the large amount adding machine 25, and the gaming machine 31
It corresponds to a mounted terminal device to which a card 400 (game information medium: recording medium) can be mounted.

The ATM exchange 15 is an information exchange device that controls the transmission of information from the management device 11, the management analysis device 12, the main repeater (indicated as a repeater in the drawing) 13, and the prize POS 14 installed in the game shop 1. Therefore, it is possible to transmit an information amount of 155 Mbps, for example, via the information transmission path 41 formed of an optical fiber. Here, ATM (Asynchrono)
us Transfer Mode: asynchronous transfer mode). Generally, high-speed operation cannot be performed in packet communication, and a signal with a very high bit rate cannot be handled. On the contrary,
The ATM exchange is based on the premise that a high quality transmission line such as an optical fiber transmission line with a low bit error rate is used. Exchange connection with a hardware switch that can operate. As a result, the semiconductor switch can be used up to the operation speed, and a signal of several hundred Mbit / sec or more can be switched and connected. Using such an ATM exchange technology, data, documents, voice,
Transfer of various types of information, such as images, images, etc., is possible in a single line.

The ATM switch 15 of this embodiment receives information from each terminal device installed in the store based on the above principle,
It performs exchange control for transmitting necessary information. The ATM exchange 15 and the information transmission line 41 composed of an optical fiber constitute a first transmission network 42 having a physically large information transmission capacity. The management device 11, the management analysis device 12, the main repeater 13, and the premium POS 14 are the first transmission network. A network connected by the transmission network 42 is configured. A system having a physically large information transmission capacity is a system that can secure an extremely large transmission capacity using an ATM switching technology and an optical fiber.

The main repeater 13 relays information transmission between the upper first transmission network 42 and the lower repeaters 21 and 22. For example, an optical repeater is used to perform communication using infrared rays. To do. The main repeater 13 is connected to the upper first transmission network 4.
2 allows 155 Mbps information transmission to and from the ATM switch 15, and 1
This is a configuration capable of transmitting 6 Mbps information. The lower repeater 21 is for relaying information transmission between the card issuer 23, the renewal machine 24, the large amount adder 25, and the main repeater 13. For example, an optical repeater is used, and infrared light is used. Perform communication. The repeater 21 can transmit information of 1 Mbps among the card issuing machine 23, the updating machine 24, and the large amount of money adding machine 25.

On the other hand, the lower repeater 22 is a gaming machine 31a-
31n, which relays information transmission between the replenishing device 32 and the main repeater 13. For example, an optical repeater is used to perform communication using infrared rays. The repeater 22 is capable of transmitting information at 1 Mbps between the gaming machines 31 a to 31 n and the supply device 32. The repeaters 21 and 22, the main repeater 13, the card issuing machine 23, the renewal machine 24, the large money addition machine 25, the gaming machines 31a to 31n, and the replenishing device 32 are wireless (here, information transmission by infrared rays). The two transmission networks 43 constitute a network. The management device 11 and the management analysis device 1 connected to the first transmission network 42 having a large transmission capacity via the ATM exchange 15 and the information transmission line 41 composed of an optical fiber.
2. The main repeater 13, the repeater 21, 22, the main repeater 13, the card issuing machine 23, the renewal machine 24, the large money adder 25, and the game which are connected to the network including the premium POS 14 by the second transmission network 43. The network including the machines 31a to 31n and the supply device 32 constitutes a LAN (local area network) as a whole, and is a system capable of mutually transferring information at a high speed.

(II) Game Hall Management System FIG. 2 is a diagram showing a game system management system. In FIG. 2, a management device 11 is an ATM switch 15 installed in a store.
Card company 2 and a telephone line 45 (for example, ISD
N or other digital lines). The management device 11 and the ATM switch 15 are connected by an information transmission line 41 composed of an optical fiber. The portion surrounded by a broken line is a configuration outside the game store, and the other game stores 46 are similarly connected to the card company 2 via the telephone line 47. The card company 2 issues an IC card common throughout the country as a game card, and performs payment for a game card in the game store 1. In addition, various information of the management device 11 in the game arcade 1 is received as needed (for example, reception of card payment information). The amusement store 1 is connected to the card company 2 via the telephone line 45 for obtaining card issuing information and necessary information from the card company 2 and making inquiries. In the following description, an IC card 400 described later is simply referred to as a game card or a card, as appropriate.

More specifically, the card company 2 issues a serial number (for example, an issue number) to a gaming card when issuing a card, security information, a temporary issuing machine number, encryption information, and an IC card control program. Is stored and issued to each amusement store. In addition to the card information, the card company 2 has a card issuing machine 23, a gaming machine 31, and an updating machine 2.
4. Large-sized money addition machine 25, identification number of premium POS 14 (individual identification information required when mutually authenticating each terminal device), card restriction information (for example, maximum value of added money:
Information such as security information is transferred to the management device 11 of each gaming shop. The individual identification information will be transmitted as an initial value to the card issuing machine 23 by the management device 11 later.

In the case of the card issuing machine 23, a temporary issuing machine number and a true issuing machine number are given, and the IC card 400 is made to recognize the card issuing machine 23 (details will be described later) by the temporary issuing machine number, When the IC card 400 is issued from the card issuing machine 23, the temporary issuing machine number is overwritten by the true issuing machine number and becomes individual identification information (that is, the issuing machine identification number) similar to other terminal devices. Amusement store 1
Is the card issuer 2 or the necessary information
From the ATM exchange 15
Is connected to the card company 2.

Here, an IC used as a game card
When the card 400 is defined, an IC card usually includes an 8-bit (or 4-bit) CPU, a data memory, and a program memory storing a predetermined program, and is a non-contact type electromagnetic coupling type. , C
This is a high-security memory medium that can perform advanced judgment, calculation, data protection, etc. by utilizing the functions of the PU. The data memory used is non-volatile, for example, rewritable EE
PROM is the mainstream. The IC is usually embedded in a thin plastic card (which may be a vinyl chloride card) so that sufficient protection can be achieved while ensuring portability. Also, unlike magnetic cards, safety and security protection are sufficiently provided. Instead of an IC card, an optical card having sufficient safety and security protection may be used. In such a case, a necessary part such as a card reader / writer is used corresponding to an optical card.

The management device 11 is arranged in the management room of the hall and includes a management computer, a display, a printer 50,
It has an external storage device 51, a terminal input device (for example, a keyboard and a mouse), and an uninterruptible power supply (UPS) 52. The management computer manages the card system from the card company 2 to the telephone line 45 and the ATM exchange 1
5, card issuing machine 23, gaming machine 31, update machine 24, large amount of money addition machine 25, prize POS1 via information transmission path 41
4 identification number, card restriction information, security information,
In addition to the process of receiving the information such as the encrypted information and transmitting it to the card issuing machine 23 and the like as an initial value, the process necessary for the management control of each terminal device of the game shop 1 is performed. Further, a process of transmitting information relating to card settlement to the card company 2 is also performed. Further, the management computer manages various card information of the issued card, and also stores and manages the verification history with the card inserted from each terminal device (for example, the gaming machine 31, the updating machine 24, etc.). The matching history with the card is cleared only on the day of our shop. The external storage device 51 stores management information regarding the card system. Further, the management computer always manages information equivalent to the card by regular communication with each terminal device. The uninterruptible power supply (UPS) 52 has a battery inside, and supplies emergency power to each circuit of the management device 11 to back up the operation for a certain time when the commercial power supply fails.

The management analysis device 12 is also arranged in the management room of the hall, and has a management analysis computer, a display,
Printer 60, external storage device 61, terminal input device (for example, keyboard or mouse), uninterruptible power supply (UPS)
It has 62. The management analysis computer is used for calculation, display, simulation processing, management analysis information display, management forecast information display (for example, screen display of information such as sales and profits of halls), operation history of the remote control device, which will be described later. ATM exchange 1 for managing information, etc.
5. Connected to each terminal device via the information transmission path 41 to receive necessary information. For example, Hall Island Unit 16
Collect the necessary data from a large number of enclosed ball-type gaming machines 31 installed in, and organize the data corresponding to various gaming states for the calculation, display, and simulation processing required for management, and perform business analysis. The result is displayed on the display 62 or printed by the printer 63. Also,
The operation information of each remote control device operated by the clerk of the amusement store is collected, and processing necessary for managing the operation information is performed.

The management analysis computer stores data collected from a large number of enclosed ball-type gaming machines 31 and each terminal device (receiving information from the management device 11) in an internal storage device as daily data or stores the data. Data is stored in the external storage device 61 or the like. For example, necessary data is collected from a large number of enclosed ball-type game machines 31 and management device 11 installed in the island unit 16 of the hall, data corresponding to various game states is arranged, and the arranged data is displayed on the display 62. Display (for example, time-series sales information,
The number of big hits for each machine type), the operating state of each gaming machine 31 (for example, error state, calling state) are monitored, and necessary data calculation processing is performed. In addition, by operating the terminal input device, the game machine results are calculated by game type, machine type, island unit, and manufacturer, and sales information, big hit data, prize ball data, etc. are collected, and a management analysis computer It can also be displayed on the display.

Then, a simulation for predicting sales is performed based on the data stored in the external storage device 61, and past sales data is called up as necessary. In addition, game information from the gaming machine 31 (eg, jackpot information, prize ball number information, etc.), prize exchange information from the prize POS 14 (eg, the amount of coins to be saved, the amount exchanged for cash, the amount exchanged for prizes, etc.) The collected data, such as the additional amount information from the additional amount machine 25, is taken in, necessary calculations are performed using the data, and processing for determining the performance of the gaming machine 31, exchange information of premiums, management information, and the like is executed. The uninterruptible power supply (UPS) 62 has a battery inside, and supplies an emergency power to each circuit of the business analysis device 12 to back up operation for a certain period of time when a commercial power supply fails.

(III) Communication System of Terminal Device FIG. 3 is a diagram showing a communication system of the terminal device. In FIG. 3, the prize POS 14 is connected to an ATM switch 15 installed in the store via an information transmission line 41 made of optical fiber, and the repeater 13 is connected to the information transmission line 4 made of optical fiber.
1 is connected to the ATM switch 15. That is, they are connected to a first transmission network 42 having a large transmission capacity and configured via an ATM exchange 15 and an information transmission line 41 composed of optical fibers. On the other hand, the main repeater 13 has a function of relaying information between the first transmission network 42 and the second transmission network 43, and each terminal device (card issuing machine 2
3, renewal machine 24, large amount adding machine 25, gaming machine 31a-
31n, the supply device 32) forms an information network via the repeaters 21 and 22 of the second transmission network 43.

The repeaters 21 and 22 are provided with an optical transmitter / receiver 71 of the card issuing machine 23, an optical transmitter / receiver 72 of the updater 24, an optical transmitter / receiver 73 of the large-sized money adder 25, and display units of the gaming machines 31a to 31n by infrared communication. 74a, 74b
The information is mutually transmitted between the optical transmission / reception units 75a and 75b and the optical transmission / reception unit (not shown) of the replenishing device 32.
The display units 74a and 74b are hereinafter simply denoted by reference numerals 74 as appropriate, and
Hereafter, a and 75b are simply represented by reference numeral 75 as appropriate. In the island unit 16, gaming machines 31a, 31b are arranged, and between-car amount adding machines 76a, 76b (hereinafter, referred to as “inter-game amount adding machines”).
The replenishing device 32 and the large-size money adding machine 25 are arranged as appropriate (simply denoted by reference numeral 76 as appropriate).

The card issuing machine 23 issues an IC card purchased from the card company 2 to a player as a game card (for example, when a player who does not have an IC card purchases one), for example, 1000 yen. Issue a game card. The issued card can be continuously used for a predetermined period (for example, one year). The card issuing machine 23 transfers game card sales information and the like to and from the management device 11 via the optical transmission / reception unit 71. Also, the card issuing machine 23 performs a mutual authentication process with the IC card at the time of issuing the card, and when it is determined that the card is valid, the card issuing machine 23, the gaming machine 31, the renewal machine 24, 25. Processing for recording the identification number of the premium POS 14, initial information of the card, and the like is performed.

The large-size money adding machine 25 is an I-purchased machine purchased by a player.
By inserting a C card and inserting coins and bills,
A desired amount is added to the IC card. First, a mutual authentication process of the IC card is performed, and the amount (valuable value) is added to the IC card based on the result. For example, any of 3000 yen, 5000 yen, and 10000 yen can be selected as the additional amount. It should be noted that the addition of money can also be performed by the inter-car money addition machine 76 arranged between adjacent gaming machines, and in this case, money is added in units of 1000 yen.

The gaming machine 31 performs mutual authentication of the IC card, and based on the result, converts the amount of money (value information of value) recorded in the IC card into the number of balls (game value information) that can be used in the game. The game is made possible by the number of balls (game value) already recorded as a result of the game, and the result of the game is recorded in the IC card. Specifically, when the IC card is inserted, information on the IC card (amount data, ball number data, etc.) is read to lend a ball, and the number of balls acquired by the player is stored in the IC card. Control the display unit 7
The ball lending (that is, sales) information and the like is transferred by the IC card to the management device 11 and the management analysis device 12 through the optical transmission / reception unit 75 of No. 4 via the network.

The front frame and the like of the gaming machine 31 can be remotely controlled by a remote control device (hereinafter referred to as a remote control device) 100, and the remote control device 100 is operated to emit infrared rays to the display unit 74 of the gaming machine 31. Then, the gaming machine 31 receives an instruction from the display unit 74.
The opening and closing of the front frame is remotely performed. In this case, the operation history information of the remote control device 100 is transferred from the optical transmission / reception unit 75 of the gaming machine 31 to the management analysis device 12 via the network. The remote control device 100 has a transmission unit capable of emitting infrared rays, a plurality of push buttons arranged on the surface of the main body, a control unit including a microcomputer, and the like. An infrared ray including the remote control ID is output, and the gaming machine 31 is remotely operated.

Further, a call switch for calling a game clerk is arranged on the display unit 74. When the call switch is operated, a call packet is transmitted from the optical transceiver 75 to the management analysis device 12 via the network. The management analysis device 12 receives the call packet. In addition, gaming machine 3
In 1, a signal is generated in accordance with occurrence / cancellation of an error and sent to the display unit 74. And
When an error occurs in the gaming machine 31, in the display unit 74, an error packet including each data of a unit number, a status, and a detailed code according to the error state is transmitted from the optical transmitting / receiving unit 75 to the management analyzer 1 via the network.
2 and the management analyzer 12 receives the error packet. Similarly, when the error is cleared, the status of the error packet is determined to determine the error clearing information. That is, when the status of the error packet is on, an error occurs, and when the status of the error packet is off, the error is released.

The error packet includes the status and detailed code data, and the detailed code is set in advance according to the type of error, but what kind of error is included is arbitrary. In this way, the error packet information including the status and the detailed code data is transmitted from the terminal device (including the game machine 31, the display unit 74, and the optical transmission / reception unit 75) called the game machine 31 to the management analysis device 12 via the network. As for the configuration, other terminal devices (that is, the prize POS 14, the card issuing machine 23, the updating machine 24,
The same applies to the large-amount adder 25 and the replenishing device 32), in which various information including the status information of the terminal device is collected and judged by the management analysis device 12, and the status information of the terminal device is displayed on the screen (notification). It is possible to do. In addition, the terminal device of the amusement arcade is not limited to the above example, and other terminal devices may be included.

The updating machine 24 is for replacing a card after a predetermined expiration date (for example, one year) with a new card in order to use the IC card without any trouble. When an IC card exceeding the limit is inserted, the IC card is disabled under a predetermined condition (here, the update permission is inquired to the card company 2 via the management device 11 and updated when the permission is issued). In addition, a new IC card is issued and a new IC card is issued, and information recorded on the IC card before collection is recorded on the new IC card. When the IC card 400 (hereinafter, simply referred to as an IC card) is inserted, the prize POS 14 performs mutual authentication of the inserted IC card, and based on the result, I
The prize exchange process is performed according to the information on the C card.
Payment can be made based on the number of balls (game value) recorded in the IC card. The reason why payment is possible is that if the ball count data recorded on the IC card does not match the data recorded on the management device 11, a prize exchange is decided through discussion between the player and the hall staff. Because,
This is because the prize exchange is not permitted in all cases.

The prize POS 14 is arranged in an unoccupied place in the hall, and a space is provided on the back side where a clerk can perform maintenance. In the prize exchange in the prize POS 14, it can be exchanged for cash or a stored amount of money (stored as amount information at the cash conversion rate of the hole) based on the number of balls held in the IC card. Can also be exchanged for cash. The replenishing device 32 is for enclosing or replenishing a plurality of gaming machines 31a to 31n arranged in the island unit 16 with an enclosed ball (FIG. 1).
reference).

(IV) Configuration of Management Analysis Device FIG. 4 is a block diagram showing the configuration of the management analysis device 12. In FIG. 4, the management analyzer 12 is mainly composed of a workstation 151, a graphic interface 152, a parallel interface 153, an audio interface 154, a SCSI host adapter 155, an ATM interface 156, an external storage device (hard disk device: HDD, etc.) 157. , An amplifier 158, a display device (CRT) 160, a printer 60 (see FIG. 2), and a speaker 162.

The workstation 151 carries out arithmetic processing necessary for management, display, simulation, management of usage history of the remote control device, etc. relating to management of the card type game system. The workstation 151 has a graphic interface 152 and a parallel interface 15.
3, the audio interface 154, the SCSI host adapter 155, and the ATM interface 156 are connected to external devices. Each interface is realized by a circuit including an IC or the like on a predetermined board (for example, a printed board).

The graphic interface 152 performs a signal conversion process for displaying an image on the display device 112. The display device 160 includes a CRT capable of color display, and displays an image based on an output signal from the graphic interface 152. As the display device 112, for example, a 20-inch CRT capable of displaying 1280 × 1024 dots is used. The parallel interface 153 is a connection unit for transferring signals to the printer 60, and the printer 60 prints and outputs necessary information and the like. The audio interface 154 is an amplifier 158.
Is a connection unit for transferring when outputting various audio signals such as audio signals and sound effects, and the amplifier 158 outputs various audio signals such as audio signals and sound effects output from the audio interface 154. Amplifies the speaker 1
Sound from 62. The SCSI host adapter 155 is a connection unit for transferring data with the external storage device 157, and the ATM interface 156 is a connection unit for transferring with the ATM exchange 15 by ATM.

Next, FIG. 5 is a diagram showing a detailed block configuration of the business analysis device 12. In FIG. 5, the workstation 151 is an MPU module 171, a BIOSR.
OM 172, timer 173, FPU 174, bus interface 175, DMA controller 176, memory bus interface 177, RAM 178, M bus 1
79, S bus 180, and memory bus 181.
The MPU module 171 reads a boot program stored in the BIOSROM 172 and boots it, and executes a program for performing calculations, display, simulation, management of the usage history of the remote control device, etc. regarding management of the card-type gaming system, and a hard disk device (HDD) 187. The data is read into the memory (RAM 178) and the processing is executed. BIO
The SROM 172 stores the boot program, and the RAM 17
8 is used as a work area. Timer 173 is M
The FPU 174 is a dedicated processor that takes charge of floating-point arithmetic and measures the time required for the arithmetic processing of the PU module 171. The FPU 174 is intended to accelerate graphic processing.

The bus interface 175 interfaces between the M bus 179 which mainly carries out data transfer centering on the MPU module 171 and the S bus 180 which mainly carries out data transfer with each interface board. The DMA controller 176 controls the DMA transfer of data to the MPU module 171 with various devices connected via the S bus 180. The memory bus interface 177 performs interface processing relating to data transfer between the M bus 179 and the memory bus 181, and the RAM 178 is connected via the memory bus 181. S bus 1 mainly for interface management
80 has a parallel interface 153, an Ethernet interface 182, and an ATM interface 1
56, FD interface 183, GPIB interface 184, audio interface 154,
The graphic interface 152, the SCSI host adapter 155, and the serial interface 185 are connected.

The Ethernet interface 182 is a connection unit for transferring a signal to / from a device forming an external LAN network (especially Ethernet). The FD interface 183 is a connection part when signals are transferred to and from a floppy disk (FD) device, and the GPIB interface 184 is an IEEE48.
This is a connection unit for transferring signals to and from a device having eight standards. SCS to SCSI host adapter 155
A hard disk device (HDD) 187 as various external storage devices 157, a magneto-optical disk device (MO) 188, a digital tape storage device (DA) via the I-bus 186.
T) 189 and a CD-ROM drive device 193 are connected. The CD-ROM drive device 193 is a CD-R
When the OM is inserted, the CD-ROM is driven to drive the CD-R.
A process of reading the information stored in the OM is performed. CD-R
The OM is supplied from, for example, a gaming machine manufacturer, and stores various setting information, gaming machine evaluation information, and the like. The serial interface 185 is a connection unit for transferring serial data, and is connected to the RS-232C board 190, keyboard 191, and mouse 192. RS
The 232C board 190 is a connection unit for exchanging signals specified by one of predetermined interface standards, for example, EIA standard 232C. Keyboard 191
Is for the operator to make necessary input, and the mouse 192 is also for input operation.

Here, the RAM 178, the hard disk device (HDD) 187, the magneto-optical disk device (MO) 18
8. Digital tape storage device (DAT) 189, CD-
The ROM drive device 193 constitutes an information storage means.
The workstation 151, the keyboard 191, and the mouse 192 constitute a prediction information change input unit and a game machine setting information information change input unit. The workstation 151 is a predicted visitor number calculation means, a predicted total used game value information calculation means, a predicted used game value information calculation means for each gaming machine, a predicted sales / profit information calculation means, a predicted gaming machine operation rate information calculation means,
A game machine setting information variable calculation means, a predicted sales / profit information recalculation means, and an information transfer means are configured. Graphic interface 152, parallel interface 153,
Audio interface 154, display device (CRT) 160, printer 60 and speaker 162
Constitutes a display means. Display unit 74,
Optical transmitter / receiver 75, repeater 21, main repeater 13, first transmission network 42, ATM interface 156, second transmission network 4
3 constitutes a terminal device information collecting means for collecting information from each terminal device and information from each gaming machine 31.

(V) Description of Data Next, various data calculated by the management analyzer 12 will be described in detail. The data includes aggregated data aggregated from the terminal device and predictive data for predicting the hall condition. "Data Aggregation" First, to explain from data aggregation, game information from the terminal device is stored in the P machine same day result file or the like formed on the internal memory (RAM 178) (memorized data only on the day), and the P machine same day result. Based on data such as files, gaming machine performance information, machine model performance information, hall performance information are aggregated or calculated as necessary. Each of these pieces of information will be described in detail below. U: All-day sales amount (model sales information, gaming machine sales information) This is the total amount of sales for one-day games. In the case of gaming machines, it is calculated for each gaming machine by the formula: total sales amount U = P machine same-day ball rental sales Ut + P machine same-day ball sales amount Uc. In the case of a model, the total daily sales amount U of the gaming machines belonging to the model is totaled. In the case of a hall, total day-to-day sales U of all models in the hall are totaled.

Ao: Total out of special prize all day (corresponding to model out ball number information, game machine out ball number information, used game value information) This is the total number of balls fired in a day's game when no big hit is in progress. In the case of a gaming machine, it corresponds to Ao for each gaming machine. In the case of a model, the Ao of gaming machines belonging to the model is totaled. Fo: Safe total outside special prize all day (corresponding to model safe ball number information, game machine safe ball number information) It is the total number of prize balls when a big hit is not in the game of one day. In the case of a gaming machine, it corresponds to Fo for each gaming machine.
In the case of a model, the Fo of gaming machines belonging to the model are totaled. Ah: Out-of-all day special out total (corresponding to model out ball number information, gaming machine out ball number information, used game value information) This is the total number of launch balls during the award in the game of one day. In the case of a gaming machine, it corresponds to Ah for each gaming machine. In the case of a model, the Ah of the gaming machines belonging to the model is totaled.

Fh: Safe all day special prize (corresponding to model safe ball number information, game machine safe ball number information) It is the total number of prize balls in the special prize in the game of one day. In the case of a gaming machine, it corresponds to Fh for each gaming machine. For models,
Fh of the gaming machines belonging to the model is totaled. S: Total number of start-ups all day This is the total number of symbol changes in the game in one day. In the case of a gaming machine, it corresponds to S for each gaming machine. In the case of a model, the S of gaming machines belonging to the model is totaled. H: Total number of jackpots throughout the day (corresponding to model special prize number information and gaming machine special prize number information) This is the total number of special prizes in the game for one day. In the case of gaming machines, it corresponds to H for each gaming machine. In the case of a model, H of gaming machines belonging to the model is totaled. A: All-day out ball total (corresponding to model out ball number information, gaming machine out ball number information, total used game value information) This is the total number of balls fired in a day's game. In the case of a gaming machine, the calculation formula is A = Ao + Ah for each gaming machine. In the case of a model, A of gaming machines belonging to the model is totaled. In the case of a hall, add up A for all models in the hall.

F: All-day safe ball total (corresponding to model safe ball number information and game machine safe number information) This is the total number of prize balls in the game for one day. In the case of a gaming machine, it is calculated for each gaming machine by an arithmetic expression of F = Fo + Fh. In the case of a model, the F of gaming machines belonging to the model is totaled. In the case of a hall, total F of all models in the hall. I: Total number of balls to be driven in all day The total number of balls to be driven in in a day's game. The number of balls to be driven is the number of balls to be driven in before one special prize is obtained. In the case of a gaming machine, I = Ao-Fo is calculated for each gaming machine. In the case of a model, I of gaming machines belonging to the model is totaled. In the case of a hall, add up I for all models in the hall. R: Total number of balls lent throughout the day This is the total number of balls lent in a day's game. In the case of gaming machines, the calculation formula is R = U / p (where p is the ball lending rate) for each gaming machine. In the case of a model, R of gaming machines belonging to the model is totaled. In the case of a hall, add up the R values for all models in the hall.

J: Total number of balls settled all day This is the total number of balls brought out from any one gaming machine in the game of one day. In this case, when leaving the gaming machine with balls, it is assumed that all the balls are settled. The number of all-day settlement balls can be calculated from the following three data. Total number of balls in the prize during the day = Fh-Ah …… Total day ball rental total = R …… Total day ball total = I …… The player wins the ball represented by the formula and the formula, Since the ball represented by is lost, the number of balls finally brought out by the player from any one gaming machine becomes a value represented by the arithmetic expression +-. Therefore, the all-day settlement ball counter is calculated as follows. All day settlement ball counter J = (Fh-Ah) + RI When this data J is expanded to the range of model and hall, it is calculated by the following method. In the case of models, J of gaming machines belonging to each model is totaled. In the case of a hall, add up the J of all models in the hall.

L: All-day payout amount The all-day payout ball counter J is multiplied by the payout rate q, which is the actual payout amount of the gaming machine (the payout amount in the one-day game). In the case of a gaming machine, the calculation formula is L = J × q for each gaming machine. In the case of a model, it is calculated for each model by an arithmetic expression of L = J × q. In the case of a hall, the calculation formula is L = J × q. V: Gross profit all day (corresponding to machine profit information and game machine profit information) This is the gross profit (prospect profit) of the game machine. The gross profit of the gaming machine in the game of one day is calculated as the difference between the all-day sales amount and the all-day refund amount. In the case of gaming machines, V = for each gaming machine
It is calculated by a calculation formula of UL. In the case of a model, it is calculated for each model by a calculation formula of V = UL. In case of hall, V =
It is calculated by a calculation formula of UL.

W: divisor The ratio of the number of settlement balls to the number of rental balls. On a daily basis, it is the ratio of the number of all-day settlement balls to the total number of all-day ball rentals. In the case of a gaming machine, it is calculated for each gaming machine by an arithmetic expression of w = J / R.
In the case of a model, it is calculated for each model by an arithmetic expression of w = J / R. In the case of a hall, the calculation formula is w = J / R. d: Ball discharge rate This is the ratio of the total number of prize balls to the total number of balls fired. On a daily basis, it is the ratio of the all-day safe meter to the all-day out meter.
In the case of a gaming machine, it is calculated for each gaming machine by an arithmetic expression of d = F / A. In the case of a model, it is calculated for each model by an arithmetic expression of d = F / A. In the case of a hall, the calculation formula is d = F / A. M: Number of difference balls This is the difference between the total number of shot balls and the total number of prize balls. In the case of a gaming machine, it is calculated for each gaming machine by an arithmetic expression of M = FA. In the case of a model, the calculation formula of M = F−A is calculated for each model. In the case of a hall, the calculation formula is M = FA.

B: Base value (sometimes simply referred to as base: model base information, game machine base information) Total number of balls fired when not a big hit (special prize) (model out ball number information, game machine out ball number information) ) And the total number of prize balls when not a big hit (machine safe ball number information, game machine safe ball number information). This data (base value) represents the degree of ball loss at normal times. The smaller the value, the faster the player's possession balls decrease. In the case of a gaming machine, b = Fo / Ao is calculated for each gaming machine. In the case of a model, it is calculated for each model by an arithmetic expression of b = Fo / Ao. s: Start-up rate It is the number of shot balls required for the special symbol display device (so-called special symbol, the same applies below) to perform one symbol variation. The smaller this numerical value (symbol starting rate), the smaller the number of balls can be changed. In the case of gaming machines, s = A for each gaming machine
It is calculated by the calculation formula of o / S. In the case of a model, it is calculated for each model by an arithmetic expression of s = Ao / S.

T: Special prize rate The number of fluctuations of symbols necessary for one special prize (special drawing big hit) to occur is represented by an average value. For gaming machines,
It is calculated by an arithmetic expression of t = S / H for each gaming machine. In the case of a model, it is calculated for each model by an arithmetic expression of t = S / H. y: Average number of coins This is the number of coins that can be obtained in one big hit. In the case of gaming machines, y = (Fh-Ah) / H is calculated for each gaming machine. For models, y = (Fh-
Ah) / H is calculated. z: Number of out balls at the time of special prize (corresponding to model out ball number information, game machine out ball number information) It is the number of shot balls consumed during one big hit. In the case of a gaming machine, z = Ah / H is calculated for each gaming machine. In the case of a model, the calculation formula is z = Ah / H for each model.

K: Prize ball game rate This is the ratio of the number of hits to the number of ball rentals. This numerical value (prize ball game rate) is determined almost uniquely by the business mode of the hall (for example, the rule of lucky number business). In the case of a gaming machine, k = I / R is calculated for each gaming machine. In the case of a model, it is calculated for each model by an arithmetic expression of k = I / R. In the case of a hall, it is calculated by an arithmetic expression of k = I / R. p: Ball lending rate This is the lending amount per ball set by the hall. For example, when lending 25 balls for 100 yen, p = 4
Becomes q: Settlement rate When changing one ball set by the hall to a prize and one ball
It is the amount of money when converting individual pieces into savings balls. For example, ball 400
If you can exchange it for a 1000 yen prize, q
= 2.5. e: Occupancy rate (model operation rate information, game machine operation rate information) This is the ratio of the actual ball firing time to the business hours of the hall. In the case of a gaming machine, when the number of out balls of the gaming machine is A and the business hours of the hall is N, it is calculated by the following formula. e = (A × 0.6) / N Further, in the case of a model, when the number of out balls of the model is A, the business hours of the hall is N, and the number of models is C, it is calculated by the following formula. e = (A × 0.6) / (N × C) Then, in the case of a hole, the number of balls out of the hole is A, the business hours of the hole is N, and the total number of gaming machines installed in the hole is C. Then, it is calculated by the following formula. e = (A × 0.6) / (N × C)

"Data Prediction" Next, data prediction will be described. First, the data of the model specification file stored in the CD-ROM is read, and the model number is added to the data to create a model game setting value file. Next, based on the created data such as the model game setting value file, the gaming machine performance prediction information and the hall performance prediction information are aggregated or calculated as necessary to perform data prediction.
Each piece of information that is the target of such data prediction will be described in detail below. In the following explanation, "dash (')"
Data marked with is predictive data. A ′: Predicted all-day out ball total (predicted total used game value information) It is a predicted all-day out ball total. In the case of a hall, guess based on the number of people visiting the store on the next business day. In the case of a gaming machine, A'of the hall is divided and calculated for each gaming machine. b ': prediction base value This is a base value for prediction.

S ': Predicted starting rate This is the predicted starting rate. t ': predicted special prize ratio It is a predicted special prize ratio. y ': predicted average payout is the predicted average payout. z ′: Number of out balls at the time of the special prize for prediction (predicted game value information for use) It is the number of out balls at the time of the special prize for prediction (that is, the number of predicted balls to be consumed during one big hit). For gaming machines,
The above-mentioned prediction base value b ', the above-mentioned predicted starting rate s', the predicted special prize rate t ', the predicted average payout ball y', and the predicted special prize-out ball number z'are all five game setting for each gaming machine. Determined depending on the value. k ': predicted prize ball game rate This is a predicted prize ball game rate. In the case of a gaming machine, it is determined depending on the rule set value set for the belonging machine.

Ao ': Predicted all-day non-prize out total (predicted used game value information) Predicted all-day non-prize out total. In the case of a gaming machine, it is calculated by the following formula. Ao ′ = A ′ / {1+ (z ′ / s ′ · t ′)} Fo ′: Predicted all-day non-special prize safe meter This is a predicted all-day non-special prize safe meter. In the case of a gaming machine, it is calculated by the following formula. Fo ′ = Ao ′ × b ′ S ′: Predicted all-day start counter This is a predicted all-day start counter. In the case of a gaming machine, it is calculated by the following formula. S '= Ao' / s 'H': Predicted all-day jackpot counter This is the predicted all-day jackpot counter. In the case of a gaming machine, it is calculated by the following formula. H '= S' / t '= Ao' / (s '· t')

A ′: Average number of out-of-prize special prizes (predicted game value information) This is the average number of out-of-prize non-special prizes (average number of outs until a big hit occurs). In the case of a gaming machine, it is calculated by the following formula. a ′ = Ao ′ / H ′ = s ′ · t ′ f ′: Predicted non-special prize average safe total Predicted non-special prize average safe total (average safe number until a big hit occurs). In the case of a gaming machine, it is calculated by the following formula. f '= Fo' / H '= s'.t'.b' i ': Predicted average number of hit balls The average number of hit balls for prediction (the average number of hit balls until a big hit occurs). In the case of a gaming machine, it is calculated by the following formula. i '= a'-f' = s'.t '-(s'.t'.b') = s'.t '* (1-b')

Ah ': Predicted all-day special award-out total (predicted use game value information) Predicted all-day special award-out total. In the case of a gaming machine, it is calculated by the following formula. Ah ′ = z ′ · H ′ = (Ao ′ · z ′) / (s ′ · t ') By the way, since the relation of A = Ao + Ah is established, A ′
Assuming that = Ao '+ Ah', the following relationship holds. A '= Ao' + Ah '= Ao' + (Ao '+ z') / (s '· t') = Ao '+ {1 + z' / (s '・ t')} Therefore, the above-mentioned prediction all-day special prize is not included. As for the out total Ao ′, the expression Ao ′ = A ′ / {1 + z ′ / (s ′ · t ′)} holds.

Fh ': Safe Total during Special All-day Prediction Total Safe during Mid-day Special Prediction. In the case of a gaming machine, it is calculated by the following formula. Fh ′ = H ′ (y ′ + z ′) = {Ao ′ (y ′ + z ′)} / s ′ · t ′ F ′: Predicted all-day safe meter It is a predicted all-day safe meter. In the case of a gaming machine, it is calculated by the following formula. F ′ = Fh ′ + Fo ′ = [{Ao ′ (y ′ + z ′)} / (s ′ · t ′)] + (Ao ′ · b ′) = Ao ′ [{(y ′ + z ′) / (s '• t')} + b '] I': Predicted all-day-impacted ball number counter This is the predicted all-day-impacted ball number meter. In the case of a gaming machine, it is calculated by the following formula. I '= i' * H '= s' * t '* (1-b') * {Ao '/ (s'.t')} = Ao '(1-b')

R ': Predicted all-day ball rental total number This is the predicted all-day ball rental total number. In the case of a gaming machine, it is calculated by the following formula. R ′ = I ′ / k ′ = Ao ′ (1-b ′) / k ′ J ′: Predicted all-day settlement ball counter This is a predicted all-day settlement ball counter. It is the predicted total number of balls brought out from any one gaming machine in the game of one day. In this case, when leaving the gaming machine with balls, it is assumed that all the balls are settled. Further, the predicted number of all-day settlement balls can be calculated from the following three data. Predicted value of the total number of balls in the prize during the day = y '× H' …… Predicted total day ball rental total = R '…… Predicted total day ball input total = I' …… The player is represented by the formula and formula The number of balls brought out from any one gaming machine by the player finally becomes a predicted value expressed by an arithmetic expression of +-, since the number of balls to be taken out is lost and the ball represented by the formula is lost. Therefore, the predicted all-day settlement ball counter is calculated as follows. J ′ = (y ′ × H ′) + R′−I ′ = Ao ′ [y ′ / (s ′ · t ′) − {1- (1 / k ′)} × (1-b ′)]

U ': forecast all-day sales amount (estimate sales information) This is the forecast all-day sales amount. In the case of a gaming machine, it is calculated by the following formula. U ′ = R ′ × p = Ao ′ · p · (1-b ′) / k ′ Further, if A ′ is used instead of Ao ′, it is expressed by the following equation. U ′ = [A ′ / {1 + z ′ / (s ′ · t ′)}] × {p
-(1-b ') / k'} In the case of a hall, U'of all the gaming machines in the hall is totaled. L ′: forecast full-day refund amount This is the forecast full-day refund amount. In the case of a gaming machine, it is calculated by the following formula. L '= J' * q '= Ao'.q. [Y' / (s'.t ')-{1- (1 /
k ′)} × (1-b ′)]

V ': Forecast all-day gross profit amount (forecast profit information) This is the forecast all-day gross profit amount. In the case of a gaming machine, it is calculated by the following formula. V '= U'-L' = Ao '[[{(1 / k') * p} + {1- (1 / k ')} * q] * (1-b')-q * y '/ (S ′ · t ′)] Further, if A ′ is used instead of Ao ′, it is expressed by the following equation. V ′ = {A ′ / (s ′ · t ′ + z ′)} × [[{(1 / k ′) × p} + {1- (1 / k ′)} × q] × s ′ · t ' -(1-b ')-q-y'] In the case of a hall, V'of all gaming machines in the hall is summed up.

W ': prediction divisor The divisor of the prediction. In the case of gaming machines, it is calculated by the following formula for each gaming machine. In case of w '= J' / R 'hole, w' = J '/ R' is calculated. d ': predicted ball output rate is a predicted ball output rate. In the case of gaming machines, it is calculated by the following formula for each gaming machine. In the case of d '= F' / A 'hole, it is calculated by d' = F '/ A'. M ′: predicted difference ball number is the predicted difference ball number. In the case of gaming machines, it is calculated by the following formula for each gaming machine. In the case of M ′ = F′−A ′ hole, M ′ = F′−A ′ is calculated.

(VI) Structure of Various Files Next, various files formed in the management analysis device 12 will be described. 6 to 52 are diagrams showing various files formed in the management analysis apparatus 12, and these files will be described in detail below. (1) POS connection file (see FIG. 6) As shown in FIG. 6A, the POS connection file stores information for identifying a plurality of terminal devices (here, the prize POS 14) in a POS connection record. is there. PO
The S connection records are created by the number of terminal devices (here, the prize POS 14) installed in the hall. As shown in FIG. 6B, the POS connection record is composed of the following data. -POS number A number for identifying the prize POS 14 (for example, the prize PO
(Identification information when multiple S14 are installed and information for identifying the terminal device) -Communication address Address on the network for managing the gift POS14-Installation status The gift POS14 is connected to the network Status information indicating that

(2) Large-sized machine connection file (see FIG. 7) The large-sized machine connection file includes information for identifying a plurality of terminal devices (here, large-sized money adding machine 25) as shown in FIG. 7 (a). It is stored in the large machine connection record.
The large-sized machine connection records are created for the number of terminal devices (here, large-sized money adding machine 25) installed in the hall.
As shown in FIG. 7B, the large machine connection record is composed of the following data. Large machine number A number for identifying the large money adder 25 (for example, identification information when a plurality of large money adders 25 are installed and information for identifying a terminal device) Communication address Large money adder 25 Address on the network for managing the installation / installation status Status information indicating whether the large-sized money addition machine 25 is connected to the network or in a broken state

(3) Issuer connection file (see FIG. 8) The issuer connection file issues information for identifying a plurality of terminal devices (here, the card issuer 23), as shown in FIG. 8A. It is stored in the machine connection record. Issuer connection records are created for the number of terminal devices (here, card issuing machines 23) installed in the hall. The issuer connection record is composed of the following data, as shown in FIG. -Issuing machine number A number for identifying the card issuing machine 23 (for example, identification information when a plurality of card issuing machines 23 are installed and information for identifying a terminal device) -Communication address Managing the card issuing machine 23 Address on the network for installation ・ Installation status Status information indicating whether the card issuer 23 is connected to the network or in a failed state

(4) Updater connection file (see FIG. 9) The updater connection file updates information for identifying a plurality of terminal devices (here, the card updater 24), as shown in FIG. 9A. It is stored in the machine connection record. Updater connection records are created for the number of terminal devices (here, the card updater 24) installed in the hall. As shown in FIG. 9B, the update machine connection record is composed of the following data. -Updater number A number for identifying the card updater 24 (for example, identification information when multiple card updaters 24 are installed and information for identifying the terminal device) -Communication address Managing the card updater 24 Address on the network for installation ・ Installation status Status information indicating whether the card updater 24 is connected to the network or in a failed state

(5) Model registration file (see FIG. 10) As shown in FIG. 10A, the model registration file is for registering the model specifications as a model registration record. The model registration record corresponds to one model,
The number of models registered in the hall will be created.
As shown in FIG. 10B, the model registration record is composed of the following data. -Model number A number for identifying the model of the gaming machine-Model code Code information for identifying the model of the gaming machine (there are only the number of models) -Model name A name indicating the model of the gaming machine

[Manufacturer Code] Manufacturer that manufactured the game machine of that model (manufacturer)
Code information for identifying the game-maker name A name that represents the manufacturer that manufactured the game machine-Game type code To identify the type of the game machine (for example, game type such as 1st type, 2nd type, 3rd type) Code information ・ Game type name Name that indicates the type of gaming machine ・ Number of game setting values Number of variable setting values such as the jackpot probability of games, probability of universal figure, etc. (for example, “5” in the case of 5 step settings)・ Number of rule setting values The number of settable sales rules (lucky number sales rules, etc.) when playing games on the model (for example, “5” when the sales rules can be set in five categories)

Here, the sales rules in the hall (for example,
Lucky number business) will be described as follows. Depending on the model of the gaming machine, some (or all) of the following rules can be set. The lucky number business is not limited to the following example. Simple lucky number game Only when the lucky number big hit (the big hit here is a special figure, the same applies below), you can play the ball game.
For example, a ball game can be played only when a big hit occurs with lucky numbers “3” and “7”. When a big hit occurs with other symbols (for example, "5"), it is necessary to exchange all the balls. Lucky number, unlucky number game Lucky number big hit occurrence (for example, "3",
"7") starts the ball game. You have no balls, or you have an unlucky number (for example,
All balls are exchanged due to the big hit in "4"). Alternatively, the player may voluntarily stop the game.

Lucky number, unlucky number, special lucky number game Lucky number (for example, "3"), special jackpot number with special lucky number (for example, "7"), the handball game is started. In the case of a ball game with a lucky number, all balls are exchanged when a big hit occurs with an unlucky number (for example, "4"). In the case of a big hit with a special lucky number, there is no exchange of balls held all day. However, when there are no balls remaining, the ball game may be invalidated or the ball game may be continuously enabled. Even if it is a special lucky number, for example, if the player changes, the ball game is invalidated. Unlimited by designated time For example, "From opening to 12:00", "2 hours before closing"
Unlimited business with limited time, etc. (ball games can be played with all patterns). Addition of a lucky number by specifying the time For example, during the period from "opening until 12:00", etc., the lucky number is usually "3" or "7" plus "5".
Is to add (or decrease).

Unlimited all day There is no exchange of balls for all jackpot designs. This is advantageous for the player. Complete one-time exchange system Even if you hit big with any design, you are forced to exchange the payout after the big hit. However, when a big hit occurs again in the starting memory after the big hit ends, the payout balls are exchanged after the big hit ends. Only unlucky numbers are set. All big hits other than unlucky numbers are unlimited, and when a big hit of unlucky numbers (for example, "4" and "9") occurs, all winning balls are exchanged. Others Quantitative system: A system that forces the exchange of balls according to the prescribed number of balls, and is also called a stop system. Probability fluctuation: It is possible to play a ball game only while the jackpot probability is increasing.

(6) Model Information File (See FIG. 11) As shown in FIG. 11A, the model information file stores information on gaming machines in the hall as a model information record. The model information record is created for each model. As shown in FIG. 11B, the model information record is composed of the following data. -Model number A number for identifying the model of the gaming machine-Number of installations Number of installations of the model in the hall

(7) Model game setting value file (see FIG. 12)
As shown in FIG. 12A, the model game setting value file stores information about the game contents of each model as a model game setting value record. For example, information on a CD-ROM distributed by the manufacturer. Is read by the CD-ROM drive device 193 (the same applies hereinafter) and registered in the hall. Model game setting value records are created for each model for the number of game setting values. The model game setting value record is composed of the following data, as shown in FIG. -Model number A number for identifying the model of the game machine-Game setting value Variable setting values such as the jackpot probability of games, probability of universal figure, etc. (for example, in the case of a 5-step setting, which value has been set, For example, a set value such as "3")-Predicted base value Predicted value of the base value corresponding to the game set value-Predicted symbol starting rate A shot ball required to perform one pattern change corresponding to the game set value Predicted value of number ・ Predicted prize probability Predicted value of probability that special map corresponding to game setting value will be a big hit ・ Predicted average number of payouts Value to predict the average number of discharged balls of the model corresponding to game set value ・ Predictive prize Medium Out Predicted value of the ball that will be out during the big hit corresponding to the game setting value

(8) Model rule set value file (see FIG. 13)
As shown in FIG. 13A, the model rule setting value file stores information on rule contents for each model as a model rule setting value record. For example, information on a CD-ROM distributed from the manufacturer. Is read by the CD-ROM drive device 193 (the same applies hereinafter) and registered in the hall. The model rule set value records are created for each model for the number of rule set values. As shown in FIG. 13B, the model rule setting value record is composed of the following data.・ Model number A number for identifying the model of the gaming machine ・ Rule setting value Variable setting of the sales rule when playing the game with the model ・ Predicted prize ball game rate The number of hits for the number of balls lent corresponding to the rule setting value Predicted value of ratio (prize ball game rate), which is read from the model specification file C described above and registered in the hall.-Rule setting content Contents of the business rule when playing a game with the model (for example, the content of unlimited). information)

(9) Model layout file (see FIG. 14) The model layout file is as shown in FIG. 14 (a).
Data that can identify which model each machine is stored as a model layout record for each machine. For example, at the time of the first new opening of a game shop, some (all may be)
A model layout record is created and stored when the store is opened when the model is replaced. The model layout record is shown in Figure 1.
As shown in FIG. 4 (b), it is composed of the following data. -Unit number A number for identifying the gaming machine-Model number A series number for identifying the model of the gaming machine

(10) Hole initial value file (see FIG. 15) As shown in FIG. 15 (a), the hole initial value file stores data necessary for ball lending and settlement in the hole as a hole initial value record. To do. The hole initial value record is composed of the following data, as shown in FIG.・ Ball lending amount of money when renting one ball (for example, 4 yen / one ball) ・ Payment rate: amount of money when converting one ball into a prize (for example, 2.5 yen /
(1 ball) and the rate when changing the accumulated amount to a monetary amount Note that this hole initial value file is placed as a shared file with the management device 11, for example, in the management device 11, and the management analysis device 12 via the network initializes the hole. Use the data by capturing the value. Not limited to this, for example, the management analysis device 12 side may hold the hole initial value file. Such a file is the same as that shown in FIGS. 15 to 20. The files after FIG. 21 are held by the management analysis device 12.

(11) Unit-to-unit addition history file (see FIG. 16) As shown in FIG. 16A, the unit-to-unit addition history file is an operation history (action Every other time, the same applies to other terminal devices hereinafter) is stored as an inter-vehicle additional history record. As shown in FIG. 16B, the inter-vehicle additional history record is composed of the following data. -Time time when the machine-to-machine amount addition machine 76 operates by adding the amount-The machine number A number for identifying the gaming machine (in this case, since the gaming machine and the machine-to-machine amount adding machine 76 are arranged in a pair, the machine number Is the identification number of the unit-to-unit price adder 76) -Card number Information that can identify the card by the series number of the IC card 400-Additional amount The amount of money added by the unit-to-unit price adder 76 (here 100
0 yen uniform)

(12) Amount-added history file (see FIG. 17) As an amount-added history file, as shown in FIG. 17A, the data of the operation history of the large amount adder 25, which is one of the terminal devices, is added. It is stored as a history record. As shown in FIG. 17B, the amount-addition history record is composed of the following data.・ Time The time when the large-sized money adding machine 25 operates by adding the amount of money ・ Large-sized machine number The identification number of the large-sized money adding machine 25 ・ Card number Information that allows the card to be identified by the series number of the IC card 400 ・ Additional money Large-sized money adding machine Amount added in 25 ・ Number of premium added balls Number of balls added in premium when adding amount to IC card

(13) Settlement history file (see FIG. 18) As shown in FIG. 18A, the settlement history file stores operation history data of the prize POS 14, which is one of the terminal devices, as an amount-added history record. It is a thing. As shown in FIG. 18B, the settlement history record is composed of the following data.・ Time The time when the prize POS14 operates by exchanging prizes ・ POS number A number for identifying the prize POS14 ・ Card number Information that allows you to identify the card by the series number of the IC card 400 Amount converted to the amount of coins saved in the prize POS14

(14) Issue history file (see FIG. 19) The issue history file stores, as an issue history record, operation history data of the card issuing machine 23, which is one of the terminal devices, as shown in FIG. 19 (a). To do. As shown in FIG. 19B, the issuance history record is composed of the following data. -Time The time when the card issuing machine 23 operates by issuing a card-Issuing machine number A number for identifying the card issuing machine 23-Card number Information that can identify the card with the series number of the IC card 400-Issue amount Card issuing machine Amount used for issuing at 23 (for example, 1000 yen)

(15) Update history file (see FIG. 20) As shown in FIG. 20A, the update history file stores the data of the operation history of the card updating machine 24, which is one of the terminal devices, as an update history record. To do. As shown in FIG. 20B, the update history record is composed of the following data. -Time The time when the card renewal machine 24 is operated for card renewal-The renewal machine number The number for identifying the card renewal machine 24-The card number is the series number of the IC card 400 to be renewed and the information that can identify the card (that is, (Old card) -New card number Information that can identify the card by the series number of the updated IC card 400 (that is, updated new card)

(16) Automatic setting file (see FIG. 21) As shown in FIG. 21A, the automatic setting file stores the game setting value data of the gaming machine as an automatic setting record for each machine. The automatic setting record is shown in Fig. 21 (b).
As shown in, it is composed of the following data. There are as many automatic setting records as there are gaming machines. -Unit number A number for identifying a gaming machine-Game setting value A variable setting value such as a big hit probability of a game, a probability of a universal figure, etc. , A setting value such as “3”) Note that the automatic setting file is placed in the management analysis apparatus 12 as a shared file with the management apparatus 11, and is taken in by the management apparatus 11 via the network and set as a setting value (initial value). Used.

(17) P machine same day result file (see FIG. 22) As shown in FIG. 22A, the P machine same day result file stores the result data of the game machine on that day as the P machine same day result record. is there. In addition, the P machine day result file is
It is stored in an internal memory (for example, RAM 178).
As shown in FIG. 22 (b), the P machine day record is composed of the following data. Note that the P machine day record is overwritten and updated in real time (that is, due to the trend of one ball). Then, every 5 minutes, the external storage device 157
The data based on the data of the P machine day record is transferred to and stored in the P machine (stored in the P machine basic file). -Unit number A number for identifying a gaming machine-Number of P-games played Number of times a game has been played on the P-game-Game status Information indicating what state the game of the P-machine is in-Prize status Information that shows how the special prize is in the game ・ Card number IC card series number (to identify the customer who played the game on the P machine) ・ P machine same day ball lending sales on the day of the P machine Sales by lending a ball

-Sales amount on the same day on P machine Sales amount from lending balls from stored coins on the P machine on the day-Number of balls collected on the P machine on the day Number of balls collected on the day on the P machine (balls for which game results have been confirmed) Number of balls out of special prize on the same day on P machine Number of balls not on special prize on the same day on P machine ・ Number of safe balls on special day on P machine on the same day Number of non-special prize balls on the day of P machine on the day of P machine Number of out balls during special prize Number of launch balls during special prize on the day on the relevant P machine ・ Number of safe balls during special prize on the same day on P aircraft Number of prize balls during special prize on the same day on the relevant P machine ・ P machine Same-day start number The number of changes in the special design pattern on the day of the day ・ Number of special prizes on the day of the P machine Number of big hits on the day of the P machine ・ Number of bonus balls on the day of the P machine Number of bonus balls on the day of the P machine

(18) Hall day result file (see FIG. 23)
As shown in Fig. 23 (a), the hole day result file is
The same day performance data of the entire hole is stored as a hole day performance record. As shown in FIG. 23 (b), the hole day result record is composed of the following data. Note that the hole day result record is overwritten and updated in real time (that is, due to the movement of one ball), and the data is a cumulative value.・ Hall operation status Information that shows how the hole is operating ・ Time of opening on the day Time of opening the hall on the day ・ Time of closing on the day Time of closing the hall on the day ・ Rate of the day ball 1 Amount for renting a piece ・ Same-day settlement rate Rate for converting one ball on the day and rate for converting one ball to a savings amount The same-day ball lending rate and the same-day settlement rate are passed from the management device 11 via the network. Then capture and store.

-Same day weather-Weather on the day of the day-Sales of ball rental on the day of the hall Sales of balls lent on the day of the hall-Sales of balls accumulated on the day of the hall Sales of balls lent from balls accumulated on the day of the hole-Same day of the hall Number of out balls on the day of the hole ・ Number of safe balls on the day of the hole ・ Number of prize balls on the day of the hole ・ Number of bonus balls on the day of the hole ・ Number of extra balls on the day of the hole ・ Number of premium balls on the day of the hole Number of balls added in premium on the day of the hole ・ Amount redeemed on the day of the hole ・ Amount redeemed by redemption on the day of the hole ・ Amount of coins accumulated on the day of the hole Amount converted to coins accumulated on the day of the hole ・ Number of visitors on the day The number of people who visited on the day

(19) Customer Same Day Result File (See FIG. 24) The customer same day result file stores, as shown in FIG. 24 (a), customer's current day result data as a customer same day result record. Further, the customer day result file is stored in the internal memory (for example, RAM1) as data of the day only.
78) and is transferred to an external storage device and stored when the store is closed. After that, the contents stored in the internal memory are erased. The customer day result record is composed of the following data, as shown in FIG. The customer day result record is overwritten and updated in real time (that is, by the movement of one ball), and the data is a cumulative value. Then, the customer day result record is created for each customer by specifying the customer. -Card number Series number of IC card that identifies the customer-Course time The time when the customer visited the hall and the card was inserted into the P machine (so-called card-in time)

-Customer Same Day Ball Rental Sales: Customer's Same Day Ball Rental Sales-Customer Same Day Savings Sales: Customer's Same Day Ball Lending Sales-Customer Same Day Out Balls Number of balls fired-Number of safe balls on the day of the customer Number of prize balls on the day of the customer-Results of winning and losing for the last month Monthly results of the last month of the customer Win / Loss result = [[(safe ball count-out ball count) + {(ball rental sales + accumulated ball sales) / ball lending rate]] x settlement rate]
-(Ball rental sales + ball sales) ・ Number of store visits in the past month The number of times the customer visited the store in the past month

(20) P machine basic file (see FIG. 25) The P machine basic file stores the result data of the P machine as a P machine basic record, as shown in FIG. 25 (a). Further, the P machine basic file is stored in the external storage device (for example, the hard disk device 187) as data for each day. The P machine basic file is created for each P machine and for each date. As shown in FIG. 25B, the P machine basic record is composed of the following data. The P machine basic record is read out from the P machine same day result file at regular time intervals (every 5 minutes), and at each timing when the card is inserted (card in) and when the card is ejected (card out). Created. The P machine basic record is created each time the customer plays a game. Therefore, even for the same customer, if the game time is different, the P machine basic record is created each time. -Time Time when the P machine basic record was created (for example, card-in time) -Event code Code information indicating the distinction of events of data collection at the P machine (for example, data collection at scheduled events, card-in event (Code information that distinguishes data collection and data collection at card-out event)

Card number Series number of the IC card used in the P machine (also used as information for identifying the customer) Blank if there is no IC card used in the P machine at the time of periodic record creation-Game Number The series number in which the game was played on the P machine ・ Cumulative sales of P machine ball rental sales Cumulative sales of ball rental by the P machine ・ Cumulative sales of P machine savings balls Lending from balls accumulated by the P machine Cumulative amount of sales-Cumulative number of P machine out balls Cumulative number of launch balls on the P machine-Cumulative number of P machine collected balls Cumulative number of collected balls on the P machine (number of balls for which game result is confirmed) -P machine Cumulative number of safe balls Cumulative number of prize balls on the relevant P machine ・ Cumulative number of times of starting P machine symbol design ・ Cumulative number of starting times of special symbols on the P machine ・ Cumulative number of bonus balls on the P machine Number of bonus balls on the P machine Cumulative of

(21) P machine result file (see FIG. 26) As shown in FIG. 26A, the P machine result file stores data indicating the results of each machine as a P machine result record for each machine. is there. Further, the P machine result file is formed by storing the result data stored in the internal memory (for example, the RAM 178) as the data of the day for each P machine in the P machine result record when the store is closed. After that, the contents stored in the internal memory are erased. Fig. 26 shows the P machine record.
As shown in (b), it is composed of the following data. -Date The date when the record record for the machine was created.The date includes the past dates from the opening of the hall to the current day.- Machine number A number for identifying the gaming machine.-Game setting value Variable setting value such as figure probability (for example, what value is set in the case of 5 steps setting, for example, setting value such as "3")-P machine ball rental sales amount Ball of the unit Sales from lending ・ Sales from P machine savings balls Sales from lending balls from the machine ・ Sales from P machines Sales from ball lending from the machines and ball lending from savings

-Number of balls collected from P machine Number of balls collected from the machine (balls for which game result is confirmed) -Number of balls out of special machine of P machine Number of shot balls out of special machine of the machine-Number of safe balls out of special machine of P machine Number of prize balls outside the special prize of the unit-Number of out balls during special prize of P machine-Number of launch balls during special prize of the target machine-Number of safe balls during special prize of P machine-Number of prize balls during special prize of the target machine-Number of times of starting P machine pattern Number of times the special design pattern of the machine fluctuates-Number of special prizes for the P machine Number of times that the machine has hit big-Number of bonus balls for the P machine Number of bonus balls for the relevant machine-Additional amount of money between the machines of the P machine The amount of money added to the IC card with

(22) P machine time series result file (Fig. 27)
As shown in Fig. 27 (a), the P aircraft time series result file is
Data indicating the results of each machine is stored as a P machine time series result record for each machine and in time series. The time-series data collection timing is every 5 minutes, and the data is the cumulative value since the opening of the hall. As shown in FIG. 27B, the P machine time series result record is composed of the following data. -Date The date when the time series performance record of the unit was created.The date includes the past dates from the opening of the new hall to the current date. Number for identifying the gaming machine ・ P machine time-series ball rental sales amount Cumulative time-series sales amount for ball lending on the machine (cumulative ball rental sales amount every 5 minutes) For the following time-series data, Cumulative amount every 5 minutes is the same ・ P machine time-series accumulated ball sales amount Time-series accumulated amount of balls lent from balls accumulated at the machine ・ P machine time-series sales amount Ball lent at this machine and ball loan from accumulated balls Time-series total sales by P-machine time-series out balls Cumulative number of time-series launch balls at this machine-P machine time-series safe balls Cumulative number of time-series prize balls at this machine-P machine time-series Number of bonus balls Time-based cumulative number of bonus balls added on the unit

(23) Model result file (see FIG. 28) As shown in FIG. 28 (a), the model result file stores data indicating the results of each model as a model result record for each model. The result record is the result data of one day. As shown in FIG. 28B, the model record is composed of the following data.・ Date The date when the record of the record was created ・ Model number Number for identifying the model ・ Number of models ・ Installation number of the model ・ Sales of model ball rentals Sales of ball lending by the model ・ Model sales Sales from ball lending from the model with balls accumulated ・ Model sales amount Sales from ball lending from the model and balls lending from accumulated balls

[Number of out-of-balls outside the model special prize] Number of shot balls out of the special prize of the model concerned ・ Number of safe balls outside of the model special prize ・ Number of prize balls outside the special prize of the model concerned ・ Number of out balls under special prize of the model Under special prize of the concerned model Number of balls fired ・ Number of safe balls during special model prize Number of prize balls during special prize for the model ・ Number of model design start times Number of times the special design pattern for the model fluctuates

-Number of special model prizes Number of big hits for the model-Number of bonus balls for the model Number of bonus balls for the model-Additional amount for each model amount Model profit Gross profit for the model ・ Rule setting value The content that can be set by the sales rules (such as the lucky number sales rule described above) when playing the game on the model, and read it from the rule setting value file described above. And what was registered at the hall

(24) Model time series result file (see FIG. 29)
(See Fig. 29 (a))
Data indicating the results of each model is stored as a model time-series result record for each model in time series. As shown in FIG. 29B, the model time series result record is composed of the following data.・ Date The date when the grade record of the model was created ・ Time Correspondence time of the record (time at which regular data is collected every 5 minutes) ・ Model number A number for identifying the model ・ Model time series ball rental sales Cumulative time-series sales by ball lending (cumulative ball-rental sales every 5 minutes) The same for the following time-series data

-Model time-series accumulated ball sales amount Cumulative time-series sales amount due to ball lending from accumulated balls in the model-Model time-series sales amount Time-series sales due to ball lending in the model and ball lending from accumulated balls Cumulative number of model time-series out balls Cumulative number of time-series launched balls in the model-Number of model time-series safe balls Cumulative number of time-series prize balls in the model-Number of model time-series bonus balls Time-series cumulative number of grants

(25) POS Result File (See FIG. 30) As shown in FIG. 30 (a), the POS result file stores data showing the final result of the prize POS 14 every day as a POS result record. The POS result record is created for each prize POS and for each date. As shown in FIG. 30B, the POS result record is composed of the following data.・ Date The date when the record record of the relevant prize POS was created.The date includes the past dates from the opening of the new hall to the current day. ・ POS number The identification number of the relevant prize POS ・ The amount of POS redemption Amount of money saved ・ POS amount saved Amount converted to savings at the prize POS

(26) Large machine result file (see FIG. 31) As shown in FIG. 31 (a), the large machine result file is a large machine result record in which data indicating the final result of the large amount money adding machine 25 every day is recorded. It is something to store. A large machine performance record is created for each large money addition machine and for each date.
As shown in FIG. 31B, the large machine performance record is composed of the following data.・ Date The date when the result record of the large amount additional machine was created.The date includes the past dates from the opening of the new hall until the day of the event. ・ Large machine number The identification number of the large amount additional machine Number of balls added as a premium with the large-sized money addition machine

(27) Issuing machine result file (see FIG. 32) As shown in FIG. 32 (a), the issuing machine result file stores data indicating the final result of each day of the card issuing machine 23 as an issuing machine result record. To do. Issuer performance records are created for each card issuer and for each date. As shown in FIG. 32B, the issue machine performance record is composed of the following data. -Date Date when the record record of the card issuing machine was created Date includes the past date from the opening of the new hall to the current day-Issuing machine number Identification number of the card issuing machine-Number of issuing cards of the card The number of IC cards issued by the issuing machine ・ Payment amount of the issuing machine card The amount paid when the IC card is issued by the card issuing machine (cumulative card issuance price)

(28) Update machine result file (see FIG. 33) As the update machine result file, as shown in FIG. 33 (a), data indicating the final result of each day of the card update machine 24 is stored as an update machine result record. To do. Update machine record records are created for each card update machine and for each date. The update machine record is composed of the following data, as shown in FIG. -Date The date when the record record of the relevant card renewal machine was created.The date includes the past dates from the opening of the new hall to the current day-Renewal machine number The identification number of the renewal machine-The number of renewal machine renewal cards Number of IC cards updated by the update machine

(29) POS time series result file (Fig. 3
4) In the POS time-series result file, as shown in FIG. 34 (a), data showing the results of each prize POS 14 is given to each prize PO.
It is stored as a POS time series result record for each S and in time series. The time-series data collection timing is every 5 minutes, and the data is the cumulative value since the opening of the hall. As shown in FIG. 34B, the POS time series record is composed of the following data. -Date The date when the time-series result record of the relevant prize POS was created. The date includes the past date from the opening of the hall to the current day.-Time The corresponding time of the record (in 5-minute increments) -POS number The prize POS Number for identifying the POS time-series exchange amount The time-series exchange amount accumulated (5
The accumulated amount for every 5 minutes is the same for the following time-series data as well. ・ The POS time-series accumulated amount of coins is the accumulated amount converted to the time-series accumulated amount of coins due to payment at the prize POS.

(30) Large machine time series result file (Fig. 3
As shown in FIG. 35 (a), the large machine time-series result file contains data indicating the performance of each large money addition machine 25 for each large money addition machine and in a time series. Is stored as. The time-series data collection timing is every 5 minutes, and the data is the cumulative value since the opening of the hall. Figure 35 for large aircraft time series records
As shown in (b), it is composed of the following data. -Date The date when the time series performance record of the relevant large amount of money added machine was created.The date includes the past dates from the opening of the new hall to the current day. Number to identify the large-sized money addition machine ・ Number of large-sized machine time-series premium added balls Amount of time series

(31) Hall date / time series result file (see FIG. 36) The hole date / time series result file is, as shown in FIG. 36 (a), data showing time series results of the entire hole in time series. It is stored as a series record. The hole date / time series result file creates a hole date / time series result record every 5 minutes.
Then, when the current day ends (for example, the closing process ends), the hall current date / time series result file is deleted.
As shown in FIG. 36B, the hole date / time series result record is composed of the following data.・ Time The time when the record record of the current date and time of the hole was created (time at which regular data was collected every 5 minutes) ・ The amount of sales on the date and time of the hole The amount of time series sales from the ball lending and savings on the day of the hole ・ The date of the hole Profitable Time-series Profit Profitable (cumulative) profit on the day at the hole for the day expected is calculated by the following formula. Expected profit = sales amount-{(safe ball number)-(out ball number)
+ (Sales amount / ball lending rate)} x (settlement rate) -Number of people visiting the store at the current date and time Cumulative number of people visiting the hall in chronological order

(32) Hall Result File (See FIG. 37) As shown in FIG. 37 (a), the hole result file stores data showing the results of the entire hole (especially the results of one day) as a hole result record. It is a thing. As shown in FIG. 37 (b), the hall record record is composed of the following data.・ Date The date when the record for the hole was created.The date includes the past dates from the opening of the hole to the day of the opening. The rate at the time and the rate at which one ball is converted to the accumulated amount of coins ・ Opening time The time when the hall was opened ・ The closing time The time when the hall was closed

-Business hours (time information) Total hours when the hall is open-Number of halls-Number of gaming machines installed in the hall-Popularity index: Ratio of the actual visitor number to the ideal visitor number to the hall-Hall ball Sales of rental balls Sales of balls lent at the hall ・ Sales of hall ball sales Sales of balls lent from balls stored at the hole ・ Hall sales Sales of balls lent at the hall and balls lent from balls ・ Hall Amount added between cars Amount added to the IC card by the machine for adding money between cars in the hall

・ Large-scale added amount of the hole Amount added to the IC card by the large-sized amount addition machine of the hole ・ Amount converted to the hole Amount converted to prizes in the hole ・ Amount accumulated in the hole Amount converted to the amount accumulated in the hole ・ Hall Number of issued cards Number of IC cards issued in the hole ・ Number of renewed cards in the hole Number of renewed IC cards in the hole ・ Gross profit in the hole Gross profit in the hole

-Number of balls added to the hole premium Number of balls added as a premium when adding money to the IC card-Number of bonus balls in the hole Number of bonus balls added in the hole-Number of balls collected in the hole Balls collected in the hole ( Number of balls whose game results have been confirmed-Number of balls out of the hole-Number of balls launched in the hole-Number of hole-safe balls Number of prize balls in the hole-Number of people visiting the number of people visiting the hole

(33) Hall time series result file (Fig. 3
As shown in FIG. 38 (a), the hole time-series result file stores, as a hole time-series result record, data indicating the results of the entire hole (especially the results of one day) in time series. Data is collected every 5 minutes and stored in hall time series performance records. As shown in FIG. 38B, the hall time-series performance record is composed of the following data. -Date The date when the time-series record of the hole was created.-Time The corresponding time of the record (in increments of 5 minutes) -Hole time-series ball lending sales Cumulative time-series sales of ball lending at the hole-Hall time-series Cumulative amount of time accumulated sales from ball lending from accumulated balls in the hole ・ Time accumulated sales from hole accumulated time series from ball lending in the hole and lending from accumulated balls

-Number of balls out of time series in the hole Cumulative number of balls in time series at the hole-Number of safe balls in time series of the hole Cumulative number of prize balls in time series at the hole-Expected profit of hole time series Expected time series at the hole Profit (cumulative) Expected profit is calculated by the above formula-Number of time-series bonus balls in the hole Number of time-series bonus points added in the hole (total) -Number of premium time-added balls in the hole IC in the hole Accumulated number of time-series balls added as a premium when adding money to the card ・ Time-series exchange amount of the hole time-series accumulated amount of time-series cash exchanged at the hole by exchanging prizes ・ Hole time-series accumulated amount of coins Converted into coins at the hole Cumulative amount of time-series ・ Number of people visiting in time-series Cumulative number of people visiting the hall in time-series

(34) Schedule calendar file (see FIG. 39)
The reference calendar file is as shown in Fig. 39 (a).
According to the calendar, the future business situation of the future hall is stored as a schedule calendar record. As shown in FIG. 39B, the schedule calendar record is composed of the following data. -Date The date corresponding to the schedule information stored in the record-Day of the week The day of the week corresponding to the above date

-Scheduled business status (open / closed) Information indicating the schedule of the hole, which is business or closed-Scheduled event Information indicating planned event of the hole-Scheduled annual event Scheduled annual event of the hole Information indicating the scheduled opening time Information indicating the scheduled opening time of the hole-Scheduled closing time Information indicating the scheduled opening time of the hole Set the scheduled opening time and scheduled closing time on the Hall information screen described below. Operate the "Register" button and the management (or operator) will input it.

(35) Practical calendar file (Fig. 40)
As shown in Fig. 40 (a), the practical calendar file is
Data indicating the status of holes along a calendar is stored as a practical calendar record. As shown in FIG. 40B, the practice calendar record is composed of the following data. -Date The date on which the actual calendar record for the hole was created-The day of the week The day on which the actual calendar record for the hole was created-Business status (open / closed) This is the information indicating the status of the hole. Information indicating the weather at the location-Events Information indicating events in the hall-Annual events Information indicating general annual events (for example, Thanksgiving Day) -Business day number After opening the new hall Total days of sales (cumulative)

(36) Hall performance prediction file (see FIG. 41)
As shown in Fig. 41 (a), the hole score prediction file is
Data for predicting the performance of the entire hall (particularly, the performance of the next business day) is stored as a hall performance prediction record. The hall performance prediction record is created when the store is closed, and at this time, the data is predicted and determined by calculation. Only one hole performance forecast record will be created for the next sales. As shown in FIG. 41 (b), the hole performance prediction record is composed of the following data.・ Hole forecast sales amount Hall forecast sales amount for the next business day ・ Hall forecast expected profit Profit expected for the next business day profit use)

-Number of balls predicted to be out: Cumulative number of balls to be predicted for the next business day hole-Number of safe balls to be predicted: Cumulative number of prize balls to be predicted for the hole on the next business day-Number of bonus balls to be predicted: Hole on the next business day Accumulated number of bonus balls ・ Total number of premium balls predicted for the hole Cumulative number of premium balls predicted for the next business day ・ Hole forecast redemption amount Cumulative redemption amount by settlement of the hole forecast on the next business day ・ Hall forecast accumulated ball amount Cumulative amount of conversions of hole forecasts to balls for next business day ・ Predicted number of visitors

(37) Hole Time-series Performance Prediction File (See FIG. 42) The hole time-series performance prediction file, as shown in FIG. The data to be predicted by is stored as a hall time series performance prediction record. The timing of creating the hall time-series performance prediction record is when the store is closed. At this time, time-series data is predicted and determined by calculation. The hall time-series performance prediction record is created for the next business, but the time-series timing is every 5 minutes. Therefore, the hall time-series performance prediction record is created with time-series cumulative value data for every 5 minutes. Fig. 42 shows the Hall time series performance prediction record
As shown in (b), it is composed of the following data. -Time Data prediction time for every 5 minutes corresponding to this record-Hole time series forecast sales amount Hall time series forecast sales amount for the next business day-Hall time series forecast expected profit Hall time series forecast profit for the next business day Profit expected from the forecast Profit expected is calculated by the above-mentioned formula (use the predicted value for the data of the formula)

-Hole time series forecast number of balls Cumulative number of balls fired in time series of holes on the next business day-Hall time series forecast number of safe balls Cumulative number of prize balls of time series prediction of holes on the next business day- Total number of bonus balls in the time series of the number of holes in the next business day ・ Total number of bonus balls in the time series for the next business day ・ Number of premium balls in the time series of the hole ・ Total number of premium balls in the time series of the next business day ・ In the hall Series forecast redemption amount Cumulative redemption amount due to settlement of time series forecasts for holes on the next business day ・ Hole time series forecast savings amount Cumulative amount of converted time series forecasts for halls on the next business day to savings balls ・ Time series forecast number of visitors Number of people visiting the hall in time series for the next business day

(38) P machine result prediction file (see FIG. 43) As shown in FIG. 43 (a), the P machine result prediction file stores data for predicting the performance of each machine as a P machine result prediction record for each machine. It is something to store. There are two records in the P machine performance forecast file, the one used on the day (created when the store was closed on the previous business day) and the one created when the store was closed on the day (prediction for the next business day). There is. As shown in FIG. 43B, the P machine performance prediction record is composed of the following data. There are as many P machine result prediction records as (P machine × 2 times). This is because the platform adjustment corresponds to the setting for the current day and the setting for the next business day.・ Prediction date The next business day for which prediction is performed ・ Unit number A number for identifying a gaming machine ・ Scheduled game settings , Which indicates the value to be set, for example, the set value that is set to "3")

-Number of predicted out-balls for P machine Number of projected balls for this machine-Number of out-balls outside P machine prediction special prize-Number of fired balls outside prediction special prize for this machine-Number of safe balls outside P machine prediction special prize Number of awards balls outside the forecast special award ・ Number of out balls in the P aircraft forecast award Special number of launch balls during the forecast award of this machine ・ Number of safe balls during the P aircraft forecast award special

-Number of times the P machine prediction symbol is started The number of times that the special symbol of the prediction of the machine fluctuates-Number of P machine prediction special prizes Number of times that the prediction of the machine is a big hit-P machine prediction prize ball game rate Ratio of the number of balls to be shot to the number of balls The value obtained from the model rule set value file for the predicted prize ball game rate corresponding to the rule set value in the model result file ・ P machine prediction special prize number The number of big hits for prediction of the machine ・ P machine prediction Profit Profit Profit expected in the unit

(39) Customer result file (see FIG. 44) As shown in FIG. 44 (a), the customer result file stores game result data when a customer visits a store as a customer result record. As a result, it is possible to know the results when the customer visits the store and plays a game. The customer record record is collected by importing and processing the data of the store visit file when the store is closed. The customer record record is composed of the following data, as shown in FIG.・ Card number Series number of the IC card that the customer came to the store and left a record (information that can identify the customer) ・ Last game date The date that the customer last played the game ・ Last visitor ball rental sales Amount of money from the ball lending used to play games when you visited the store

-Sales amount when the customer visited the store last time Sales amount by lending balls from the balls used to play a game when the customer visited the store last time-Number of out balls when the customer visited the store last time The game when the customer visited the store last time The number of balls fired when the customer visited the store ・ The number of safe balls when the customer visited the store last time The number of awards balls when the customer played the game when the customer visited the store last time ・ The record of losing or losing in the past month Number of store visits per month Number of visits by the customer in the past month

-Sales amount for the past month Sales amount by ball lending used to play games for the customer in the past month-Amount redeemed for the past month The amount redeemed for cash for the customer in the past month.・ Past amount of money saved in the past month The amount converted into savings for the customer in the past month ・ Number of visits to the customer in the past 3 months ・ Number of visits to the customer in the past 3 months ・ Playing time in the past 3 months Game time ・ Total number of store visits Total number of store visits of the customer in the past

(40) Time series unit time file (see FIG. 45)
As shown in FIG. 45 (a), the time series unit time file is
The time when creating time series data for one day is stored as a time series unit time record. The time series unit time record is created every 5 minutes from the opening of the store, and the time series unit time record is created every 5 minutes. The time-series unit time file is deleted in one day (for example, at the end of the closing process), and then the file for the next business day is created. The time series unit time record is shown in FIG. 45 (b).
As shown in, it is composed of the following data.・ Time The time to create a time-series unit time record of the hall (every 5 minutes after opening)

(41) Remote control history file (see FIG. 46) As shown in FIG. 46 (a), the remote control history file stores the usage history of the remote control device 100 as a remote control history record for each event. That is, when the store clerk operates the remote control device 100, one remote control history record is created for each operation and stored in the remote control history file in chronological order (that is, stored in chronological order here). Only). As shown in FIG. 46B, the remote control history record is composed of the following data.

Date: Date (year / month / day) when the clerk operates the remote control device 100-Time Time when the clerk operates the remote control device 100- Platform number A number for identifying the gaming machine-Remote control ID The remote control device 100 is identified ID number assigned to the number for operation / operation code Code information for identifying the operation content of remote control device 100

(42) P machine detailed error registration file (see FIG. 47) As shown in FIG. 47 (a), the P machine detailed error registration file deals with error contents in advance in case an error occurs in the P machine. The method information is stored as a P machine detail error registration record. Upon receiving the error packet from the P machine, it becomes possible to immediately display the error message and the like on the screen. The P machine detailed error registration file is read from the CD-ROM supplied by the game machine manufacturer. Alternatively, the manager may create a P machine detail error registration record by operating the "register" button on the hall information screen. P
As shown in FIG. 47B, the machine detail error registration record is composed of the following data.

Detailed Error Code As shown in FIG. 48, code information created in advance corresponding to the error state of the P machine (for example, “00000001”)
Error code: As shown in FIG. 48, the name of the error that occurred on the P machine (for example, a jamming error) • How to deal with the error that occurred on the P machine as shown in FIG. A message indicating the method (for example, "Please open the panel and remove the ball") Note that Fig. 48 shows a part of the information, and in addition to this, there is a lot of information corresponding to the P machine detail error registration record. The illustration is omitted.

(43) Next Business Setting File (See FIG. 49) The next business setting file includes the data for setting the target for the next business day, the next business hall target record and the next business P machine, as shown in FIG. 49 (a). It is stored as a target record. Management sets goals. The next sales hall target record is composed of the following data, as shown in FIG. 49 (b). The predetermined data can also be input and reset by the manager (for example, the target sales amount for the hall, the expected profit for the hall).・ Hall target sales amount The target sales amount of the hole on the next business day ・ Hall forecast sales amount The predicted sales amount of the hole on the next business day ・ Hall target expected profit The target profit of the hole on the next business day・ Forecast profit for the hole Prospect profit for the hole on the next business day

The next sales P machine target record is shown in FIG.
As shown in (c), it is composed of the following data.
The data of the planned game setting value can be input and reset by the manager. -Unit number A number for identifying the gaming machine-Scheduled game setting value Scheduled setting values such as the jackpot probability and general figure probability of the game (for example, in the case of a five-step setting, indicating which value to schedule) For example, the set value to be set to "3")-P machine predicted out ball number-Predicted number of balls for this machine-P machine predicted base value Base machine predicted value for this machine

-P machine prediction symbol starting rate Number of projected balls required for one pattern change of the machine-P machine prediction special prize probability Probability of a big hit of prediction of the machine-P machine predicted average number of balls Number of prediction balls obtained in one special prize of ・ P machine forecast special prize out number of balls in the special prize of this machine ・ P machine forecast sales amount P machine forecast sales amount ・ P machine forecast Profitable profit Expected profit for the unit

(44) Virtual file of hall results (Fig. 50)
As shown in Fig. 50 (a), the hall result virtual file is
When there is no past data when a new hall is opened, virtual hall performance data is stored as a hall performance virtual record as sample data. The hall result virtual file is read from the CD-ROM supplied by the gaming machine manufacturer when the system of the management analyzer 12 is introduced. As shown in FIG. 50B, the hall record virtual record is composed of the following data.・ Date Virtual hall target record date ・ Day of week The day corresponding to the above date ・ Number of visitors Virtual number of people visiting the hall

(45) Platform adjustment item file (see FIG. 51) As shown in FIG. 51 (a), the platform adjustment item file is for adjusting the platform (P machine) in preparation for the next business when the hall is closed (for example, nails). Adjustment items for performing adjustment, setting change of jackpot probability, etc.) are determined in advance and stored as a table adjustment item record. As shown in FIG. 51B, the platform adjustment item record is composed of data of item code 1 to item code 5. Each item code is code information corresponding to the content of an item for adjusting the base (for example, nail adjustment, setting change of jackpot probability, etc.). The item code can be changed and can be increased or decreased.

(46) Platform adjustment data file (see FIG. 52) As shown in FIG. 52 (a), the platform adjustment data file is used to adjust the platform (P machine) in preparation for the next business when the hall is closed (for example, nails). The table adjustment data (that is, the adjustment contents) when performing the adjustment, the change of the jackpot probability setting, etc. is stored as a table adjustment data record. As shown in FIG. 52B, the platform adjustment data record is composed of the following data. There are as many machine adjustment data records as there are P machines. Further, the data in these platform adjustment data records is transmitted to the display unit 74 arranged for each platform, displayed on the screen (screen of the display unit 74), and platform adjustment is performed by viewing the screen. Is able to. -Unit number Number for identifying the gaming machine-Left platform number Number for identifying the gaming machine located on the left side of the gaming machine (blank if none) -Right platform number Game located on the right side of the gaming machine Number for identifying the machine (blank if none) -Item code 1 to item code 5 Corresponding code information of the contents of the item (for example, nail adjustment, jackpot probability setting change, etc.) for adjusting the platform as described above.

[0135] This time previous result first item data to this time previous result fifth item data Contents of each previous setting result of the gaming machine for the first item data to fifth item data • Current day setting first Item data-current day setting fifth item data First item data-fifth item data setting contents of the current day of the gaming machine (that is, the data predicted last time) -current day result first item data -Current day result fifth item data First item data-Each day's setting result contents of the game machine for the fifth item data (that is, result data of the current day) -This unit next setting first item data-this Next setting 5th item data of each unit Setting contents of each item of the 1st item data to 5th item data of the next business day of the game machine (that is, the forecast data of this unit for the next business) Pedestal day Results first item data-left stand day results fifth item data first item data to fifth item data corresponding game machine on the left side of the table on the day of each setting on the results content (i.e.,
Right platform result data on the same day) -Right platform result 1st item data to right platform same day result 5th item data 1st item data to 5th item data each setting of the right platform of the game machine on that day Result content (that is,
Right-side result data of the day) ・ Model average day result 1st item data ~ model average current day result 5th item data 1st item data ~ 5th item data Setting result contents (that is, average result data of the model on the day)

Next, the operation will be described. A. Main Program of Business Analysis Apparatus FIG. 53 is a flowchart showing a main program of the business analysis apparatus 12. This program is a management analyzer 1
It will be started at the same time when the power of 2 is turned on. When the program of FIG. 53 starts, first, in step S10, the system initialization process of the workstation (WS) 151 in the management analyzer 12 is performed. For example, after performing a system check, a process of loading an OS (operating system) and the like to start the system is performed, and an environment variable of the workstation 151 is set.
Initialize each part of workstation 151 circuit,
The flag is reset. In addition, at this time, a process of previously creating various basic screens as described later is performed. The created screen is displayed by pop-up, and data is captured in the screen and displayed promptly.

Next, in step S12, the main screen process is activated. The main screen process is for performing processing necessary for business analysis and history management of the remote control device 100.
Details will be described later. Then, in step S14, the data collection process is activated. Data collection process is management device 1
1. Receives and collects necessary data from the gaming machine 31 and the like, and performs necessary processing when opening and closing the store. Next, in step S16, it is determined whether or not there is a power outage, and if it is not a power outage, the process proceeds to step S18 and it is determined whether or not there is an instruction to terminate the system. The system termination instruction is issued from the main screen process. If there is no instruction to terminate the system, the process returns to step S16 and is repeated. If there is an instruction to terminate the system, the process proceeds to step S20.

Also, when it is determined that there is a power failure in step S16, the process proceeds to step S20. In step S20, system shutdown processing is performed. This is because after storing all the necessary data in the external storage device 157 and saving the data, performing the processing necessary to complete the processing of each part of the circuit of the workstation 151, and after shutting down the system. The processing such as shifting to a sleep mode that consumes less power is performed. After the system shutdown processing, the system is terminated, the system shifts to the sleep mode, and the system is ready for the next startup (for example, opening the store tomorrow). Instead of the sleep mode, the workstation 151 may be turned off and completely shut down.

B. Main Screen Process FIG. 54 is a flowchart showing the main screen process. In the main screen process, first, main screen appearance processing is performed in step S30. This pops up the main screen (so-called top screen) created in advance,
The date and the like are displayed on the screen. Next, in step S32, main screen event processing is performed. This causes a corresponding screen to appear in response to a button operation on the main screen. Next, the processing from step S34 onward is performed, but each processing is performed in step S of the main screen process.
It is executed every time 32 to step S54 is repeated.

In step S34, hall information screen event processing is performed. This is to perform processing according to the button operation on the hall information screen when the hall information screen (so-called multi-window screen) appears on the main screen, and the necessary calculations and screens corresponding to the button operation. Processing is performed. Next, in step S36, business daily report screen (1) event processing is performed. This is to perform processing according to the button operation on the business daily report screen when a business daily report screen (a so-called multi-window screen, the same applies below) that displays daily sales of the hall appears.
Necessary calculations and screen processing are performed in response to button operations.

Next, in step S38, hall data analysis screen event processing is performed. This is to perform processing according to the button operation on the hole data analysis screen when the hole data analysis screen for analyzing the hole data appears. Necessary calculation and screen processing are performed corresponding to the button operation. . Next, in step S40, model-specific advice screen event processing is performed. This is, when a model-specific advice screen that can display a sales advice message appears based on data such as sales by model of the gaming machine 31, performs processing according to a button operation on the model-specific advice screen. In this case, necessary calculations and screen processing (including displaying an advice message) are performed in response to button operations.

Next, in step S42, model detailed information screen event processing is performed. This is to perform a process corresponding to a button operation on the model detailed information screen when a model detailed information screen capable of displaying detailed information about the model of the gaming machine 31 appears. Various calculations and screen processing (including displaying detailed model information) are performed. Next, in step S44, customer information screen event processing is performed. This is to perform processing according to the button operation on the customer information screen when a customer information screen that can display detailed information about the customer's situation in the hall appears. Various calculations and screen processing (including displaying customer information) are performed.

Next, in step S46, customer fixation status screen event processing is performed. This is to perform processing according to the button operation on the customer fixation status screen when a customer fixation status screen that can display detailed information about the customer fixation status in the hall appears, and corresponds to the button operation. Required calculations and screen processing (including displaying customer retention status)
Is performed. Next, in step S48, model-specific customer status screen event processing is performed. This is to perform processing according to the button operation on the model-specific customer status screen when a model-specific customer status screen capable of displaying detailed information about the customer status for each model of the gaming machine 31 appears. Necessary calculations and screen processing (including display of customer status by model) are performed in response to the operation.

Next, in step S50, remote controller usage screen event processing is performed. This is the remote control device 10
When a remote controller usage status screen that can display detailed information about the usage status of 0 appears, the processing according to the button operation on the remote controller usage status screen is performed. Screen processing (including display of remote controller usage status) is performed. Then, step S
At 52, setting screen event processing is performed. This is game machine 3
When a setting screen that allows input of basic setting values (eg, initial value of base value, model name, calendar, etc.) that is the basis of business management data related to 1 appears, processing according to button operation on the setting screen The necessary calculation and screen processing (including display for various settings) are performed corresponding to the button operation. That is, the setting value is input on this setting screen. As the set value, information that must be stored in advance in order to analyze the business data for business related to the gaming machine 31 is input. For example, when a setting screen appears, the contents (game machine setting values, etc.) such as a model specification file A (not shown) created in advance by a game machine manufacturer and stored in a CD-ROM and distributed to a game shop are read. By storing it in the storage device (for example, the hard disk device 187) of the business analysis device 12, the process of setting the contents of the model specification file A and the like is performed. The same applies to the setting of other information, for example, the gaming machine 31.
Information that must be set in advance in order to analyze the business data in business related to is input and set.

Next, in step S54, registration screen event processing is performed. This is for registering various kinds of information, and when a registration screen in which the registration information can be input appears, a process corresponding to a button operation on the registration screen is performed. At this time, necessary calculations and screen processing (including display for various registrations) are performed corresponding to button operations. For example, the employee name data or the like regarding the remote control device 100 is input and registered according to the button operation on the registration screen. In this way, necessary input and registration are performed in advance on the registration screen. After step S54, the process returns to step S32 and the same loop is repeated.

C. Data Collection Process FIG. 55 is a flowchart showing the data collection process. The data collection process is performed by the management device 11, the gaming machine 31,
It receives data from each terminal device and a command from the management device 11 and performs necessary processing. In the data collection process, first, offline processing is performed in step S100 (details will be described later in a subroutine). This is the process when the management analysis device 12 is powered on, but the network with the management device 11 and the gaming machine 31 is not formed (when the line is not connected). For example, the management device 11 waits for a line connection. It is in the state of waiting for a command from. Next, a store opening preparation process is performed in step S102 (details will be described later in a subroutine). This is for waiting for a packet for opening preparation from the management device 11 after the lines are connected and a network with the management device 11 and the game machine 31 is formed.

Next, in step S104, store opening waiting processing is performed (details will be described later in a subroutine). This is processing such as receiving a store opening instruction from the management device 11. Next, in-step processing is performed in step S106 (details will be described later in a subroutine). This is for collecting information necessary for business analysis and various information used for operation history management of the remote control device 100 during the hall business.
Next, in step S108, a closing confirmation process is performed (details will be described later in a subroutine). This is a process of preparing for closing. Next, in step S110, the counting process 1 is performed (details will be described later in a subroutine). This is to collect actual data including the current day. The actual data includes past data other than the current day (for example, all past data including yesterday). The aggregated data is stored in the external storage device 157 (for example, the hard disk device 1).
87, a magneto-optical disk device (MO) 188, and a digital tape storage device (DAT) 189).

Next, in step S112, post-closure business processing is performed (details will be described later in a subroutine). This is to perform necessary business processing after closing the store such as setting a sales target for the next day. Next, in step S114, platform adjustment data transfer processing is performed (details will be described later in a subroutine). This is because the management analysis device 12 has aggregated various data necessary for machine adjustment (for example, base value), so that each gaming machine 31
The display unit 74 is transferred to each display unit 74. Thereby, the clerk can easily perform nail adjustment and the like of the table while watching the table adjustment data displayed on the display unit 74 of each table. Next, in step S116, the aggregation process 2 is performed (details will be described later in a subroutine). This is to perform a data totalization process on the data for the current day and the past data collected in the totalization process 1 for necessary recalculation, processing, and the like. After step S116, the process returns to step S100. Returning to step S100 means that this data collection process is one routine from the opening of the hall to the closing of the hall.
It means that it is executed on a daily basis. In this way, the actual data from the management device 11 and the gaming machine 31 is collected, and the actual data is recalculated and aggregated as necessary.

D. Offline Processing FIG. 56 is a flowchart showing a subroutine of offline processing in the data collection process. In the off-line processing, the hole operating status data of the hole day result file is set to "offline" in step S120.
As a result, the management analysis device 12 is powered on, but at the stage where the network between the management device 11 and the gaming machine 31 is not formed (the line is not connected), the command from the management device 11 waits for the line connection. I'll be waiting. Next, in step S122, it is determined whether or not the line test packet is received, and if not received, step S
Return to 120 and repeat the loop. When the line test packet is received, this loop is terminated and the process returns to the data collection process. As a result, the data collection process proceeds to the subsequent processing.

E. Store Opening Preparation Process FIG. 57 is a flowchart showing a subroutine of store opening preparing process in the data collection process. In the opening preparation processing, in step S130, the hall operating state data of the hall day result file is set to "opening preparation". As a result, after the lines are connected and the network with the management device 11 and the gaming machine 31 is formed, the state of waiting for the opening preparation packet from the management device 11 is set. Next, in step S132, data other than the hole operating status data in the hole day result file is initialized. This is to start collecting data of the hall result file on the day, so first of all, the data area other than the hall operating state data is cleared to prepare to store the data from the opening of the store.

Next, in step S134, the P machine day result file and the customer day result file are similarly initialized.
As a result, the data areas of the P machine same day result file and the customer same day result file are cleared, and preparations for storing the data from the opening of the store are made. Next, in step S136, the ball lending rate and the settlement rate data are acquired from the hole initial value file and stored in the hole day result file.
Since this is not always the same ball lending rate and settlement rate every day, each rate is received from the management device 11 and set in the hall day result file when the store is opened. Next, in step S138, a "opening preparation completion" packet is transmitted to the management apparatus 11. As a result, the management apparatus 11 confirms that the business analysis apparatus 12 has completed the preparations for opening the store. After step S138, the process returns to the data collection process.

F. Store Opening Waiting Process FIG. 58 is a flowchart showing a subroutine of store opening waiting process in the data collection process. In the store opening waiting process, in step SS140, the hall operating state data of the hole day result file is set to "open store waiting". Thereby, the management analysis device 12, the management device 11, the gaming machine 31
A network between them is formed, and a state of waiting for a store opening command from the management device 11 is entered. Then, step S1
In step 42, it is determined whether or not an opening packet has been received. If not, the process returns to step S140 to repeat the loop. When the opening packet is received, this loop is terminated and the process returns to the data collection process.

G. Processing During Business FIG. 59 is a flowchart showing a subroutine of processing during business in the data collection process. In the in-business process, first, in step S150, the in-business process is initialized (details will be described later in a subroutine). This sets, for example, an initial state for performing processing during business.
Next, in step S152, the emission data collection process is performed (details will be described later in a subroutine). This is to collect the number of balls fired toward the game board from the data of the game machine 31. Next, in step S154, a collected data collection process is performed (details will be described later in a subroutine). This is to collect, from the data of the gaming machine 31, the number of balls for which the game result has been determined by dropping the game board (for example, including balls that have won and balls that have not won: that is, collected balls). .

Next, in step S156, winning data collection processing is performed (details will be described later in a subroutine). this is,
Among the data of the gaming machine 31, the number of prize balls associated with winning is collected. Next, in step S158, remote control data collection processing is performed (details will be described later in a subroutine). This collects information on the operation status of the remote control device 100. Next, in step 160, board information data collection processing is performed (details will be described later in a subroutine). this is,
Addresses are assigned to each prize hole on the game board to collect information on which prize hole the ball entered, start prize, start of symbol fluctuation of special map, end of symbol fluctuation of special map, start of big hit, big hit The information such as the end of is collected.
Next, in step S162, analysis data collection processing is performed (details will be described later in a subroutine). This is the management device 11
Receives regular data transmitted every 5 seconds from, for example, if there is a premium when the amount of money is added to the IC card 400, the total number of premium added balls, the total number of people visiting the store, the total amount of exchanged money, and the accumulated balls The cumulative value of the amount of money data is received and stored (for example, the data of the same-day result file of the hall in the management analysis device 12 is overwritten).

Next, in step S164, call information reception processing is performed (details will be described later in a subroutine). This is to receive the call information when a store clerk call button near each display unit 74 is operated. Next, in step S166, error information acceptance processing is performed (details will be described later in a subroutine). This is to receive and accumulate an error when an error occurs in the gaming machine 31. When the error recovery is received, the accumulated information is erased. Next, in step S168, a game reference data providing process is performed. This is to transmit information (for example, the number of big hits, etc.) that can be disclosed to the player among various information collected by the management analysis device 12 to each display unit 74. Game reference data is provided. Next, a constant time process is performed in step S170 (details will be described later in a subroutine). This is a process of storing data from the internal memory (RAM 178) to the external storage device 157 (for example, the hard disk device 187) every 5 minutes, and backing up the data (data is saved in the P machine basic file every 5 minutes. Processing).

Next, in step S172, a game start data collection process is performed (details will be described later in a subroutine). This is for collecting the game start time (card-in time), starting table number, card number, etc. when the player inserts the IC card 400 into the game machine 31 and starts the game. Next, in step S174, a game end data collection process is performed (details will be described later in a subroutine). This is for collecting the time when the game ends (card-out time), the ending table number, the card number, etc. when the player ejects the IC card 400 from the gaming machine 31 and ends the game. Next, a ball lending usage data collection process is performed in step S176 (details will be described later in a subroutine). This collects usage data (sales data) for the amount of balls lent out from the balance of the IC card 400 for the table played by the player.

Next, in step S178, a stored coin usage data collection process is performed (details will be described later in a subroutine). This is for collecting usage data (sales data) from the accumulated amount of coins when the player rents out balls from the accumulated amount of money of the IC card 400 for the table played. Then
In step S180, it is determined whether or not the closing packet is received. If the closing packet is not received, step S1
When the process returns to step 52 and the process is repeated to receive the closing packet, the process proceeds to step S182 to perform the final process of the business process (details will be described later in a subroutine). This is a process for making settings for shifting to the next process. After step S182, the process returns to the data collection process.

G-1. Initialization Processing of Business Processing FIG. 60 is a flowchart showing a subroutine of initialization processing of business processing in business processing. In the initialization process of the in-business process, first, in step S200, the opening date data of the day (for example, 10 am
(Hour 00 minute) is stored. Next, in step S202, the hole operating state data of the hole day result file is switched to "in operation". As a result, a network between the terminal devices including the management analysis device 12, the management device 11, and the game machine 31 is formed, and the management analysis device 12 is in operation.
Next, in step S204, the in-business screen process is activated (details will be described later in a subroutine). This allows each screen that can be displayed during the opening of the hall to appear in parallel with the data collection. After step S204, the process returns to the in-business process.

G-2. Firing Data Collection Process FIG. 61 is a flowchart showing a subroutine of the firing data collection process in the business process. In the launch data collection process, first, in step S210, it is determined whether or not a launch packet is received. If no launch packet is received, the routine of this time is ended and the process returns to the business process. When the emission packet is received, the process proceeds to step S212, and the unit number data is acquired from the reception packet (emission packet, the same applies hereinafter). This identifies the firing of the ball and the platform from which it was fired. Then, step S
At 214, the special condition data of the P machine day result file corresponding to the acquisition machine number is checked. Next, in step S216, it is determined whether or not the special prize state is a special prize. If the special prize is being received, in step S218, it is received in the P machine today special prize out ball number data of the P machine current day result file corresponding to the acquisition machine number. Add the number of shot balls in the packet. This is performed each time a ball is fired during each of the special prizes, whereby the number of out-balls during the special prize on the P machine day special prize is cumulatively added one by one.

On the other hand, if the prize is not being awarded, step S220.
The number of shot balls in the received packet is added to the number-of-outside-balls-out-of-special-balls number data of the P-machine same day result file corresponding to the acquisition machine number. This is performed every time a ball is fired outside the special prize, so that the data of the number of out-of-special prize-out balls on the day of the P machine during the special prize is cumulatively added one by one. Step S218 or Step S22
After 0, next, in step S222, card number data corresponding to the acquisition machine number is acquired from the P machine current day result file. This identifies a customer who is playing a game with the gaming machine having the acquisition stand number. Next, step S2
At 24, the number-of-out-of-the-day balls output from the received packet is added to the number-of-out-of-the-day ball data of the same-day customer file corresponding to the acquired card number. This is to identify a customer who is playing a game with the gaming machine having the acquisition unit number, and cumulatively add one by one to the customer day out ball number data in the customer day result file of the identified customer.

Then, in step S226, the customer day win / loss result data is updated using the out, safe, ball lending sales, accumulated ball sales, ball lending rate, and settlement rate. The customer day win / loss result is calculated from the following formula for calculating the customer day win / loss result described above. Customer Day Loss Results = [[(Safe Balls-Out Balls) +
{(Ball lending sales + savings ball sales) / ball lending rate}] x settlement rate]-(ball rental sales + savings ball sales) Next, in step S228, the hole day-out ball number data of the hole day result file is received. Add the number of shot balls in the packet. As a result, the hole day result file is updated. After step S2288, the process returns to the in-business process.

G-3. Collected Data Collection Processing FIG. 62 is a flowchart showing a subroutine of collected data collection processing in the processing during business. In the collected data collecting process, first, in step S230, it is determined whether or not a collected packet is received. If the collected packet is not received, the routine of this time is ended and the process returns to the business process. When the collection packet is received, the process proceeds to step S232 and the unit number data is acquired from the received packet (collection packet, the same applies hereinafter). This identifies the collection of balls and the collection platform. Then, step S
At 234, the number-of-collected-balls data of the received packet is added to the number-of-collected-balls collected on the P-machine on the same day of the P-machine same day result file corresponding to the acquisition machine number. This is performed every time the balls that have been shot are collected, so that the number-of-collections-of-P-machine-day collected balls is cumulatively incremented by one. After step S234, the process returns to the in-business process.

G-4. Winning Data Collection Processing FIG. 63 is a flowchart showing a subroutine of winning data collection processing in the processing during business. In the winning data collection process, it is first determined in step S240 whether or not a winning packet has been received. If no winning packet has been received, the routine of this time is ended and the process returns to the business process. When the winning packet is received, the process proceeds to step S242 and the machine number data is acquired from the received packet (winning packet, the same applies below). This specifies that the ball has won and the table on which the prize has won. Then, step S
At 244, the prize status data of the P machine day result file corresponding to the acquisition machine number is checked. Next, in step S246, it is determined whether or not the special prize state is a special prize. If the special prize is being received, in step S248, the safe machine number data during the P machine day special prize of the P machine day result file corresponding to the acquisition machine number is received. The award ball count data of the packet is added. This is done every time a ball wins a safe prize during the special prize, so that the P
The number of prize balls in the special prize on the day of the machine is cumulatively added by the number of prize balls.

On the other hand, if the prize is not being awarded, step S250.
And the prize ball number data of the received packet is added to the P machine today special safe ball number data of the P machine same day result file corresponding to the acquisition machine number. This is performed every time a ball wins a safe prize outside the special prize, whereby the number of special prize outside prize balls on the P machine day during the special prize is cumulatively added by the number of prize balls. After step S248 or step S250, in step S252, card number data corresponding to the acquisition machine number is acquired from the P machine current day result file. This identifies a customer who is playing a game with the gaming machine having the acquisition stand number. Next, in step S254, the prize ball number data of the received packet is added to the customer same day safe ball number data of the customer same day result file corresponding to the acquired card number. This is to identify a customer who is playing a game with the gaming machine having the acquisition unit number, and cumulatively add the number of award balls to the customer day safe ball number data of the customer day result file of the identified customer. Next, in step S256, the customer day win / loss record data is updated using the out, safe, ball lending sales, accumulated ball sales, ball lending rate, and settlement rate. The customer day win / loss result is calculated from the above-mentioned customer day win / loss result calculation formula. Next, in step S258, the prize ball number data of the received packet is added to the hole day safe ball number data of the hole day result file. As a result, the hole day result file is updated. After step S258, the process returns to the in-business process.

G-5. Remote Control Data Collection Process FIG. 64 is a flowchart showing a subroutine of remote control data collection process in the business process. In the remote control data collection process, first, in step S270, it is determined whether or not a remote control packet has been received. If no remote control packet has been received, this routine is ended and the process returns to the open process. On the other hand, when the remote control packet is received, the following step S2 is performed according to the content of the received packet.
Of 72 to step S280, the record of the corresponding file is updated. In step S272, bonus ball data update processing is performed (details will be described later in a subroutine). This is a process of updating the file storing the current day information of the gaming machine by adding the number of bonus balls when there is a "bonus" service by operating the remote control device 100. In step S274, a remote control history record is generated. In this case, when the remote control device 100 is operated, a remote control history record corresponding to the operation history is generated each time.

In step S276, all the data of the received packet (remote control packet, the same applies hereinafter) is stored in the generated record. This stores all the data of the received packet as it is in the corresponding generated record. In step S278, the current date and the current time are stored in the generated record. As a result, the date and the current time of the day are added and stored in the generated record every time an event occurs in remote control device 100. In step S280, the generated record is stored in the remote control history file. As a result, when the remote control device 100 is operated, the generated records to which the date of the current day and the current time are added every time an event occurs are sequentially stored in the remote control history file in time series. After step S280, the process returns to the in-business process.

G-6. Bonus Ball Data Update Processing FIG. 65 is a flowchart showing a subroutine of bonus ball data update processing in the processing during business. In the bonus ball data updating process, first, in step S290, the operation code data of the remote control packet is checked. The operation code data of the remote control packet is code information corresponding to the operation content of the remote control device 100, for example, “0001”.
If the operation code data is, the operation item is "ball replenishment", if the operation code data is "0002", the operation item is "bonus ball", and if the operation code data is "0003", the operation panel is "open panel". It corresponds to. As a result, by checking the operation code data, the operation item performed by remote control device 100 is identified.

Next, in step S292, it is determined whether or not the operation code is "bonus ball", and if it is not "bonus ball", the routine of this time is ended and the process returns to the business process. If the operation code is "bonus ball", step S
In step 294, the machine number data is acquired from the remote control packet. This specifies that the remote control operation has been performed and the table on which the remote control operation has been performed. Next, in step S296, a prescribed bonus ball additional unit number (for example, 2 pieces: setting is free) is added to the P aircraft day bonus ball number data of the P aircraft day result file corresponding to the acquisition machine number. This is performed every time the bonus balls are operated by the remote control device 100, and the bonus ball number data on the P machine day is cumulatively added unit by unit. Next, in step S298, the specified number of bonus ball addition units is added to the number of bonus ball data on the day of the hole in the hole day result file. As a result, each time the bonus balls are operated, the bonus day ball number data is cumulatively added by the unit number. After step S298, the process returns to the in-business process.

G-7. Panel Information Data Collection Process FIG. 66 is a flowchart showing a subroutine of the panel information data collection process in the business process. In the board information data collection processing, first, in step S300, it is determined whether or not the board information packet is received. If the board information packet is not received, the routine of this time is ended and the processing returns to the business process. On the other hand, when the board information packet is received, the machine number data is acquired from the received packet (board information packet, the same applies hereinafter) in step S302. This is to identify the board for collecting the board information and the board for collecting the board information. Next, in step S304, the board information status data of the received packet is checked. The board information status data is information indicating the game state of the game board (for example, symbol fluctuation, big hit start, big hit end, etc.).

Next, in step S306, it is determined whether or not the board information status data is "design variation". If "design variation", in step S308 the P machine corresponding to the acquisition machine number is the P machine of the same day result file. Update the symbol start count data on the day by "+1". As a result, every time the symbol variation of the special symbol is performed, the data of the number of symbol start-ups on the P machine day is “+”.
Only 1 ”is cumulatively added. After step S308, the process returns to the in-business process. If the board information status data is not "symbol fluctuation" in step S306, the process proceeds to step S310 to determine whether the board information status data is "big hit start". If it is a "big hit start", the process branches to step S312 and the data of the number of P machine special day prizes in the P machine same day result file corresponding to the acquisition machine number is "+".
Update only 1 ”. As a result, every time a big hit occurs, the P machine day special prize count data is cumulatively added by "+1".

Next, in step S314, the special prize state data of the P machine current day result file corresponding to the acquisition machine number is changed to "special prize in progress". As a result, when a big hit occurs,
The special prize status data is in the state of "special prize". After step S314, the process returns to the in-business process. If the board information status data is not "big hit start" in step S310, the process proceeds to step S316 to determine whether the board information status data is "big hit end". If “big hit end”, the process proceeds to step S318, and the special prize state data of the P machine day result file corresponding to the acquisition machine number is changed to “out of special prize”. As a result, when the big hit ends, the special prize state data becomes a state of "out of special prize". After step S318, the process returns to the in-business process.

G-8. Analysis Data Collection Process FIG. 67 is a flowchart showing a subroutine of the analysis data collection process in the business process. In the analysis data collection process, it is first determined in step S320 whether an analysis packet has been received. The analysis packet is sent from the management device 11 as regular data every 5 seconds. If the analysis packet is not received, the routine of this time is ended and the process returns to the business process. When the analysis packet is received, the process proceeds to step S322, and the data of the hole day result file is overwritten with the premium additional ball number, the number of customers visiting the store, the redemption amount data, and the accumulated ball amount data of the received packet (analysis packet, the same applies hereinafter). This is another terminal device (card issuing machine 2
3. The data collected by the management device 11 from the prize POS 14, etc.) is overwritten on the data of the hall day result file of the management analysis device 12. After step S322, the process returns to the in-business process.

G-9. Call Information Reception Process FIG. 68 is a flowchart showing a subroutine of the call information reception process in the business process. In the call information reception process, it is first determined in step S330 whether a call packet has been received. The call packet is transmitted from the gaming machine when the customer (player) playing the game on the gaming machine 31 operates the calling switch in order to call (or cancel the calling) the clerk. When canceling the call, the clerk may operate the call switch. If the call packet has not been received, this routine is terminated and the process returns to the business process.

When the calling packet is received, the calling status of the calling packet is checked in step S332. Next, if the calling status is ON in step S334, the process proceeds to step S336, and the data other than the representative position of the interrupt event monitoring area is shifted backward. The interrupt event monitoring area is a machine number, when an event such as a call or an error occurs in the gaming machine 31,
A predetermined area as shown in FIG. 69 provided on the internal memory for monitoring the order of occurrence of events, the contents of events, and the like. In the example of the interrupt event monitoring area shown in FIG. 69,
Each item shows the following information. -Position number Position information corresponding to the order in which events are received For example, the latest received event is "0", the previously received event is "1", and the previously received event is "2". Can be decided

-No. No. for identifying a gaming machine-Event code Code information for identifying events such as calling and error occurrence For example, all errors such as ball jamming errors are "errors" and a call switch to call a clerk When is operated, it becomes “call”. -Detail code Code information for indicating the details of the event For example, when an event code called an error is received, the details of the error are unknown as it is, so the detail code informs "clogging". The representative position of the interrupt event monitoring area refers to the position number = “0”. Therefore, the event at the representative position corresponds to the latest event.

In step S336, the data other than the representative position of the interrupt event monitoring area is shifted backward, so that the events with position numbers "1" and "2" are shifted backward and the position number is "2". ,
It shifts from "3". Next, in step S338, the data at the representative position is moved to the position of position number "1". As a result, the latest position (position number =
"0": In other words, the representative position) is empty. Then, step S
At 340, the unit number data of the packet is stored in the representative position,
Set the event code to "call". As a result, the information of the calling packet received this time is at the latest position (position number = "0": representative position).
After step S340, the process returns to the in-business process.

On the other hand, if the call status is not ON in step S334 (for example, when it is OFF), it is determined that the information is call release information, the process branches to step S342, and the packet unit number from the interrupt event monitoring area is set. All the data related to the matching “event code = call” is deleted. As a result, the packet information of the unit for which a call request has been made is deleted. Then, in step S344, the data behind the interrupt event monitoring area is shifted forward to fill the erased and empty area. Thereby, for example, when the packet information of the position number “2” is deleted, the position number = “2”
Since the position is empty, the position numbers are "3" and "4".
That event shifts forward and the position numbers shift from "2" to "3". Step S344
After that, it returns to the processing during business.

G-10. Error Information Accepting Process FIG. 70 is a flowchart showing a subroutine of the error information accepting process in the business process. In the error information reception process, first, in step S350, it is determined whether an error packet has been received. Error packet is game machine 31
When an error occurs in, the game machine sends it. When the error is released, the error status described later turns off in response to the error release. If no error packet has been received, this routine is terminated and the process returns to the in-business process. When the error packet is received, the error status of the error packet is checked in step S352. Next, if the calling status is ON in step S354, the flow advances to step S356 to shift the data other than the representative position of the interrupt event monitoring area backward. As a result, the position number is "1",
The event "2" shifts backward and the position numbers shift from "2" to "3".

Then, in step S358, the data at the representative position is moved to the position of position number "1". As a result, the latest position (position number = "0": representative position) is vacant. Next, in step S360, the packet number data and detailed code data of the packet are stored in the representative position, and the event code is set to "error". As a result, the information of the calling packet received this time is at the latest position (position number = "0": representative position).
After step S350, the process returns to the in-business process. On the other hand, the error status is ON in step S354.
If not (for example, when it is OFF), it is determined that the information is for error cancellation, and the process branches to step S362, and "unit number matches", "detail code match", and "from the interrupt event monitoring area". Delete all the data of the position number "event code = error". As a result, the packet information for which the error has been requested so far is erased. Next, in step S364, the data behind the interrupt event monitoring area is shifted forward to fill the erased and empty area. As a result, for example, when the packet information with the position number “2” is deleted, the position with the position number = “2” is vacant, and the events with the position numbers “3” and “4” are shifted forward respectively. And the position numbers deviate from "2" and "3". After step S364, the process returns to the in-business process.

G-11. Fixed Time Processing FIG. 71 is a flowchart showing a subroutine of the fixed time processing in the processing during business. In the fixed time processing, first, in step S370, it is determined whether or not the fixed time is reached. The fixed time is a timing every 5 minutes from the opening of the store, and in order to transfer the data in the memory to the external storage device 157 and store it in the corresponding file every 5 minutes, the fixed time is determined. is there. If it is not the fixed time, the process returns to the processing during business hours. If it is a fixed time, the process proceeds to step S372 to store the current time in the time-series unit time file. As a result, the time at which the data is transferred is stored in the time-series unit time file. Next, in step S374, "constant time" is set in the event data used in the P-machine basic file update processing. This is to notify that it is data at a fixed time.

Then, in step S376, the P machine basic file update process 1 is performed (details will be described later in a subroutine).
As a result, the data of the P machine basic file is updated every 5 minutes. Next, in step S378, a hole day / time series result record is generated. This creates a record that stores cumulative data for every 5 minutes. Next, in step S380, the hole day ball rental sales amount, the accumulated ball sales amount, the number of out balls, the number of safe balls, from the hole day result file,
Acquire data on the number of people visiting the store, the ball lending rate, and the settlement rate. This is to store time series data every 5 minutes,
The necessary data is read out.

Next, the sum of the ball lending sales amount and the accumulated ball sales amount data acquired in step S382 is stored in the generation record (hereinafter, the same) generated in step S378 as hole date / time series sales amount data. Next, in step S384, a profit is calculated using each data of the sales amount, the number of out balls, the number of safe balls, the ball lending rate, and the settlement rate, and the profit is stored in the generated record as the hole current date / series expected profit data. Next, in step S384, the number-of-stores visitor data is stored in the generated record as the number-of-stores data for number of store visits on the current day of the hall. Next, in step S386, the current time is stored in the generated record. Next, in step S388, the generated record is stored in the hole date / time series result file.
In this way, predetermined data (data in the hole day result file) on the memory is stored as a generated record in the hole day / time series result file every 5 minutes.
After step S388, the process returns to the in-business process.

G-11-1. P machine basic file update processing 1 FIG. 72 is a flowchart showing a subroutine of P machine basic file update processing 1 in the constant time processing. In the P machine basic file update processing 1, first, in step S390, P
Create a basic record. Then, step S392.
Store the event data in the generated record created in.
Event data refers to data resulting from an event that updates the data, that is, data indicating a fixed time (events in time series of 5 minutes), a card-in event, and a card-out event. Next, in step S394, the current time is stored in the generated record. As a result, the occurrence time of the event data is stored, and the event data is also stored. Next, in step S396, the data of the P machine day result file of the P machine is stored in the generated record. As a result, the data of the P machine day result file is stored in the generated record due to the event. Then, in step S398, the generated record is stored in the P machine basic file corresponding to the P machine. As a result, the P machine basic file is updated due to this event.

G-12. Game Start Data Collection Process FIG. 73 is a flowchart showing a subroutine of the game start data collection process in the business process. In the game start data collection process, it is first determined in step S400 whether a game start packet has been received. The game start packet will be received when a card is inserted in the game machine. When the game start packet is not received, this routine is ended and the process returns to the business process. When the game start packet is received, the process proceeds to step S402 and the machine number data is acquired from the received packet (game start packet, the same applies below). This is to specify the table for starting the game. Next, in step S404, the game state data of the P machine day result file corresponding to the acquisition machine number is changed to "in game", and the card number data of the received packet is stored in the card number data.

Next, in step S406, it is checked whether the card number of the received packet is registered in the customer day result file. This is to check whether or not the customer is playing a game for the first time on the day at the hole. In step S408, it is determined whether the card number is registered in the customer day result file based on the check result. If not registered, the card number of the received packet is registered in the customer day result file in step S410. This corresponds to the state where the customer is playing the game for the first time on the day. Next, in step S412, the current time is set in the store arrival time data of the customer day result file. This is to leave the data of the customer's visit time. Then
In step S414, "game start" is set in the event code data used in the P machine basic file update process 2.
Next, in step S416, P machine basic file update processing 2 is performed (details will be described later in a subroutine). This allows
The P machine basic file is updated. After step S416, the process returns to the in-business process.

G-13. Game End Data Collection Process FIG. 74 is a flowchart showing a subroutine of the game end data collection process in the business process. In the game end data collection process, it is first determined in step S430 whether a game end packet has been received. The game end packet will be received when the card is ejected from the gaming machine. When the game end packet is not received, this routine is ended and the process returns to the business process. When the game end packet is received, the process proceeds to step S432 and the machine number data is acquired from the received packet (game end packet, the same applies below). This identifies the table at the end of the game. Next, in step S434, the game status data of the P machine current day result file corresponding to the acquisition machine number is changed to "out of game". Next, in step S436, card number data is acquired from the received packet. This identifies the customer. Next, in step S438, "game end" is set in the event code data used in the P-machine basic file update process 2. Next, step S44
At 0, P machine basic file update processing 2 is performed (details will be described later in a subroutine). As a result, the P machine basic file is updated. After step S440, the process returns to the in-business process.

G-13-1. P machine basic file update processing 2 FIG. 75 is a flowchart showing a subroutine of P machine basic file update processing 2 in the game start data collection processing and the game end data collection processing. In the P machine basic file update process 2, first, in step S450, a P machine basic record is generated. This is to create a new record because the game is started. Then, step S45
The event code data is stored in the record generated in 2. For example, if the game is started, "game start" is stored, and if the game is finished, event code data "game finished" is stored. Next, in step S454, the current time is stored in the generated record. Next, in step S456, the data of the P machine day result file of the P machine is stored in the generated record. Next, in step S458, the card number data is stored in the generated record (identification of customer). Then, in step S460, the P
The generated record is stored in the P machine basic file corresponding to the machine, and the process returns to the game start data collection process or the game end data collection process. In this way, the P machine basic file at the start of the game or at the end of the game is updated by specifying the customer.

G-14. Ball Rental Usage Data Collection Processing FIG. 76 is a flowchart showing a subroutine of ball rental usage data collection processing in the processing during business. In the ball lending use data collection process, first, in step S470, it is determined whether a ball lending use packet has been received. The ball lending use packet will be received when a ball lending is performed with a card (ball lending amount in card information, that is, additional amount). If the ball lending use packet is not received, the routine of this time is ended and the process returns to the in-business process. When the ball lending use packet is received, the process proceeds to step S472 and the unit number data is acquired from the received packet (ball lending use packet, the same applies hereinafter). This identifies the table for ball lending.

Then, in step S474, the ball lending usage amount data of the received packet is added to the P machine today ball lending sales amount data of the P machine same day result file corresponding to the acquisition machine number.
This is for accumulating ball lending usage amount data every time a ball lending is performed. Then, in step S476, P
Acquire the card number data corresponding to the acquisition unit number from the machine day result file. This is to identify the customer. Then, in step S478, the ball rental usage amount data of the received packet is added to the customer same day ball rental sales data of the customer same day result file corresponding to the acquired card number. As a result, the ball rental usage amount data is cumulatively added each time a customer is specified and a ball is lent. Next, step S480
Out, safe, ball rental sales, savings ball sales, ball lending rate,
Update the winning / losing record data on the customer day using the settlement rate. The customer day win / loss result is calculated from the above-mentioned customer day win / loss result calculation formula. Next, in step S482, the ball lending use amount data of the received packet is added to the hole day ball lending sales amount data of the hole day result file. As a result, the hole day result file is updated by identifying the customer. After step S482, the process returns to the in-business process.

G-15. Collecting Ball Usage Data Collecting Process FIG. 77 is a flowchart showing a subroutine of collecting coin usage data in the in-business process. In the collected coin use data collection process, first, in step S500, it is determined whether or not the accumulated coin use packet is received. The packet used for coins will be received when lending from the amount of coins stored in the card. If you do not receive the packet using coins,
The routine of this time is ended, and the process returns to the business process.
When the packet use packet is received, the process proceeds to step S502 to obtain the machine number data from the received packet (packet use packet, the same applies hereinafter). This is to identify the table for the use of coins.

Next, in step S504, the accumulated coin spending amount data of the received packet is added to the accumulated machine sales amount data of the accumulated machine day in the accumulated machine day result file corresponding to the acquisition machine number.
This is to cumulatively add the accumulated amount data of accumulated coins every time the balls are lent from the accumulated amount of coins. Next, in step S506, the card number data corresponding to the acquisition machine number is acquired from the P machine same day result file. This is to identify the customer. Next, in step S508, the accumulated coin usage amount data of the received packet is added to the accumulated customer sales amount data on the same day of the customer same day result file corresponding to the acquired card number. As a result, the accumulated amount data of accumulated coins is cumulatively added each time a customer is specified and balls are lent from the accumulated coins. Then, in step S510, out, safe,
The customer day win / loss result data is updated using the ball lending sales, the savings ball sales, the ball lending rate, and the settlement rate. The customer day win / loss result is calculated from the above-mentioned customer day win / loss result calculation formula. Next, in step S512, the accumulated ball usage amount data of the received packet is added to the accumulated hole day sales data of the hole day result file. As a result, the hole day result file is updated by identifying the customer. Step S5
After 12, the process returns to the in-business process.

G-16. Final Process of Business Process FIG. 78 is a flowchart showing a subroutine of the final process of the business process in the business process. In the final process of the in-business process, first, the in-business screen process is stopped in step S520. As will be described later, the business-in-progress screen process opens various sub-screens on the main screen in multiple windows. By stopping the business-in-progress screen process, the sub-screen is closed and only the main screen is displayed. After that, it returns to the processing during business.

H. Closing Confirmation Process FIG. 79 is a flowchart showing a subroutine of the closing confirmation process in the data collection process. In the closing confirmation processing, first, in step S530, the current time is stored in the closing time data of the same day of the hall day result file. This is the time when the closing packet was received. Next, in step S532, the hall operating status data of the hall day result file is set to "checking for closing". As a result, the hall operation status data changes from "in operation" to "in closing confirmation". Next, in step S534, the closing screen process is activated. As a result, a store closing screen process, which will be described later, is activated and processing required when the store is closed is performed. Next, in step S536, hole operating state data is acquired from the hole day result file. In this case, the data "closing confirmation" is acquired. Next, step S5
At 38, it is determined whether the data is "total 1".
The “total 1” is a process of totaling the data of the day, predicting the number of people visiting the store, and predicting the number of operating halls and gaming machines (the number of out balls). If it is not “Summarization 1” in step S538, the process returns to step S537 and repeats the processing. As a result, the process shifts to the aggregation process 1 of the data collection process.

I. Aggregation Processing 1 FIG. 80 is a flowchart showing a subroutine of aggregation processing 1 in the data collection process. In the aggregation processing 1, the predetermined file is updated in each of steps S540 to S554, and steps S556 to S556 are executed.
At 560, prediction processing of predetermined data is performed. Details of both will be described later in subroutines. That is, in step S540, the practical calendar file update process, in step S542 the P machine result file update process, in step S544 the model result file update process, in step S546 the POS result file update process, in step S548 the large machine result file update process, step The issuing machine result file update process is performed in S550, the updating machine result file update process is performed in step S552, and the hole result file update process is performed in step S554. In step S556, the next business day visitor number prediction process is performed, in step S558, the next business day hall operating number forecast process is performed, and in step S560, the next business day stand operating number forecast process is performed. After step S560, the process returns to the data collection process.

I-1. Practical Calendar File Update Process FIG. 81 is a flowchart showing a subroutine of the practical calendar file update process in the aggregation process 1. In the practical calendar file update process, first, step S570.
Create a practical calendar record with. This is to add a new practice calendar record. Next, in step S572, the data of the current day is acquired from the scheduled calendar file, and the data is stored in the generated record. The schedule calendar file stores data of future schedules, from which data of the scheduled day is acquired. On the other hand, the practice calendar file is a collection of past data. Next, step S5
At 74, the data of the hole day result file is stored in the generated record. Next, in step S576, the latest business day number is updated and stored in the generated record. Next, in step S578, the generated record is added to the practice calendar file. As a result, the data of the day enters the practice calendar file as a generated record, is stored as the data of the past business day, and the practice calendar file is updated.

I-2. P Machine Result File Update Processing FIG. 82 is a flowchart showing a subroutine of the P machine result file update processing in the aggregation processing 1. In the P machine result file update processing, first, in step S580, the unit number is acquired from the model layout file. This is because the pedestals of the halls are sequentially specified. Next, in step S582, a P machine result record is generated. This is to add the record of the P machine because the performance data of the P machine is added as that of the business day when the store is closed. Next, in step S584, the machine number and the date of the current day are stored in the generated record, and in step S586, the data of the P machine current day result file is stored in the generated record. As a result, the result data of the P machine is stored in the generated record newly generated in this routine.

Then, in step S588, all the records of the unit number are taken out from the unit-to-unit addition history file, and the total value of the additional amount is stored in the generated record. As a result, the cumulative value of the inter-vehicle added amount of money for the P machine is stored in the generated record. Next, in step S590, the generated record is added to the P machine result file. As a result, today's business day data is added as a record to the result file of the P machine (that is, today's result is added as a record). Next, in step S592, the next unit number is acquired from the model layout file. This is to move to the next machine since the update of the result file of the P machine is completed. Next, in step S594, it is determined whether or not all the units have ended. Since only one unit has ended in the first routine, the process branches to NO in step S58.
Return to 2 and repeat the same loop. Then, when the processing of all the units is completed, the determination result of step S594 is YES.
Then, the process returns to the aggregation process 1. In this way,
Today's performance is added as a new generated record for all halls, and the P machine performance file is updated.

I-3. Model Result File Update Process FIG. 83 is a flowchart showing a subroutine of the model result file update process in the aggregation process 1. In the model result file update process, first, in step S600, the model number is acquired from the model information file. This is to identify the model of the hall one after another. Next, in step S602, a model result record is generated. This is to add the record of the model because the grade data of the model is added as that of the business day when the store is closed. Next, in step S604, the model number and today's date are stored in the generated record, and in step S606, the machine numbers of all P machines belonging to the model are acquired from the model layout file. This identifies all the units that belong to the model.

Next, in step S608, the current day data of all P machines belonging to the model are acquired from the P machine result file. Then, in step S610, all Ps belonging to the model are
Machine data is summed up for each item, and the total value of each is stored in the generated record. This is because the performance data of all P machines belonging to the model is stored in the generated record newly generated in this routine. Next, step S6
At 12, the generated record is added to the model result file. As a result, today's business day data is added as a record to the model grade file of the model (that is, today's grade is added as a record). Next, in step S614, the next model number is acquired from the model information file. This is to move to the next model because the model result file for the model has been updated. Then
In step S616, it is determined whether or not the process (process of updating the model result file) has been completed for all models, and since only one model has been completed in the first routine, NO
To step S602, and the same loop is repeated. Then, when the processing of all the models is completed, the determination result of step S616 becomes YES and the process returns to the aggregation processing 1. In this way, the results of today for all models of the hall are added as a new generated record, and the model result file is updated.

I-4. 84. POS Result File Update Process FIG. 84 is a flowchart showing a subroutine of the POS result file update process in the aggregation process 1. POS
In the grade file update process, first, in step S620, P
Obtain the POS number from the OS connection file. this is,
The prize POS 14 (particularly, when there are a plurality of prizes POS, the prize POS is abbreviated as POS as appropriate hereinafter) is specified. Then, in step S622, POS
Generate grade records. This is the POS when the store is closed
The record data of the POS is added as the record data of that business day. Next, in step S624, the POS number and today's date are stored in the generated record. Next, in step S626, all the records of the POS number are extracted from the settlement history file, and the total sum of the redemption amount and the accumulated amount is stored in the generated record. This is because the performance data related to the POS is stored in the generated record newly generated in this routine.

Next, in step S628, the generated record is added to the POS result file. As a result, today's business day data is added as a record to the POS result file of the POS (that is, today's result is added as a record). Next, in step S630, the next POS number is acquired from the POS connection file. This is to move to the next POS since the POS result file of the POS has been updated. Next, in step S632, it is determined whether or not the processing (processing for updating the POS score file) has been completed for all POSs, and only one POS has been completed in the first routine.
The process branches to NO and returns to step S622 to repeat the same loop. Then, when the processing of all POSs is completed, the determination result of step S632 is YES and the aggregation processing 1
Return to In this way, today's results for all POS are added as new generated records,
The grade file is updated.

I-5. Large Machine Result File Update Processing FIG. 85 is a flowchart showing a subroutine of the large machine result file update processing in the aggregation processing 1. In the large machine result file update processing, first, in step S640, the large machine number is acquired from the large machine connection file. this is,
The large-sized amount adding machine 25 (particularly, when there are a plurality of large-sized amount adding machines, the large-sized amount adding machine will be simply referred to as a large-sized machine hereinafter) is specified. Next, step S6
At 42, a large machine performance record is generated. This is to add the record of the large-sized machine because the result data of the large-sized machine is added as that of the business day when the store is closed. Next, in step S644, the large machine number and the date of the day are stored in the generated record. Next, step S6
At 46, all the records of the large machine number are taken out from the amount addition history file, and the total sum of the number of premium added balls and the added amount is stored in the generated record. this is,
This is because the performance data related to the large machine is stored in the generated record newly generated in this routine.

Next, in step S648, a generated record is added to the large machine result file. As a result, today's business day data is added as a record to the large machine performance file of the large machine (that is, today's performance is added as a record). Next, in step S650, the next large machine number is acquired from the large machine connection file. This is to move to the next large machine since the update of the large machine result file of the large machine has been completed. Next, in step S652, it is determined whether or not the processing (the processing of updating the large machine result file) is completed for all the large machines, and in the first routine, only one large machine is completed.
The process branches to NO and returns to step S642 to repeat the same loop. Then, when the processing of all the large-sized machines is completed, the determination result of step S652 is YES and the aggregation processing 1
Return to In this way, today's results for all large machines are added as new generated records, and the large machine result file is updated.

I-6. Issuing Machine Result File Updating Process FIG. 86 is a flowchart showing a subroutine of the issuing machine result file updating process in the totaling process 1. In the issuing machine result file update processing, first, in step S660, the issuing machine number is acquired from the issuing machine connection file. this is,
The card issuing machine 23 (particularly, when there are a plurality of card issuing machines, the card issuing machine will be simply referred to as an issuing machine hereinafter) is specified. Then, step S662.
Generate the issuing machine performance record. This is because the record data of the issuing machine is added as the business day data of the issuing machine when the store is closed. Next, in step S664, the issuing machine number and the date of the current day are stored in the generated record. Next, step S66
In step 6, all the records of the issue machine number are retrieved from the issue history file, and the total number of records and the total sum of the issued amount are stored in the generated record. This is because the performance data related to the issuing machine is stored in the generated record newly generated in this routine. The total number of records is stored in order to detect (count) the number of issued cards.

Then, in step S668, the generated record is added to the issuing machine result file. As a result, today's business day data is added as a record to the issuing machine result file of the issuing machine (that is, today's result is added as a record). Next, in step S670, the next issuer number is acquired from the issuer connection file. This is to move to the next issuing machine since the update of the issuing machine result file of the issuing machine is completed. Next, in step S672, it is determined whether or not the processing (processing of updating the issuing machine result file) has been completed for all issuing machines, and in the first routine, only one issuing machine has been completed.
The process branches to NO and returns to step S662 to repeat the same loop. Then, when the processing of all issuing machines is completed, the determination result of step S672 is YES and the aggregation processing 1
Return to In this way, today's results for all issuing machines are added as new generated records, and the issuing machine result file is updated.

I-7. Update Machine Result File Update Processing FIG. 87 is a flowchart showing a subroutine of update machine result file update processing in the aggregation processing 1. In the update machine result file update processing, first, in step S680, the update machine number is acquired from the update machine connection file. this is,
The card updating machine 24 (particularly, when there are a plurality of card updating machines, the card updating machine will be simply referred to as an updating machine hereinafter) is specified. Then, step S682.
Generate update machine performance record with. This is because the record data of the update machine is added as the business day data of the update machine when the store is closed. Next, in step S684, the update machine number and the date of the current day are stored in the generated record. Then, step S68
In step 6, the total number of records of the update machine number is extracted from the update history file and stored as the number of updates in the generated record. This is because the record data related to the update machine is stored in the generated record newly generated in this routine. Also, storing the total number of records is
This is to detect the number of updated cards.

Then, in step S688, the generated record is added to the update machine result file. As a result, today's business day data is added as a record to the update machine result file of the update machine (that is, today's result is added as a record). Next, in step S690, the next update machine number is acquired from the update machine connection file. This is to move to the next update machine since the update of the update machine result file of the update machine is completed. Next, in step S692, it is determined whether or not the processing (processing of updating the update machine result file) has been completed for all the update machines. Since only one update machine has been completed in the first routine,
The process branches to NO and returns to step S682 to repeat the same loop. Then, when the processing of all update machines is completed, the determination result of step S692 becomes YES and the totalization processing 1
Return to In this way, the results of today for all update machines are added as a new generated record, and the update machine result file is updated.

I-8. Hall Result File Update Processing FIG. 88 is a flowchart showing a subroutine of hole result file update processing in the aggregation processing 1. In the hole score file updating process, first, a hole score record is generated in step S700. This is to add the hole performance record because the performance data of the hole is added as that of the business day when the store is closed. Next, in step S702, all model numbers are acquired from the model information file. This identifies the model of the hall in order to obtain the performance data of all models. Next, in step S704, the same-day data of all models are acquired from the model result file, the data of all models acquired in step S706 are summed up for each item, and the respective total values are stored in the generated record. As a result, the performance data of all the models of the day will be stored in the generated record newly generated in this routine. With the above processing, the data for the gaming machine is stored in the generated record, and the same processing is then performed for the terminal device.

That is, in step S708, all POS numbers are acquired from the POS connection file. This is all PO
In order to obtain S's performance data, the POS of the hall (prize P
OS14) is specified. Then, step S
At 710, the current day data of all POSs are acquired from the POS result file, the data of all POSs acquired at step S712 are totaled for each item, and the respective total values are stored in the generated record. As a result, the result data of all POSs on the current day are stored in the generated record newly generated in this routine. With the above processing, the data regarding the free gift POS has been stored in the generated record, and the same processing is then performed for other terminal devices. In step S714, all large machine numbers are acquired from the large machine connection file. This is to specify the large-sized machine (large-sized money adding machine 25) in the hall in order to obtain the performance data of all large-sized machines. Next, in step S716, the same-day data of all large machines are acquired from the large machine result file, the data of all large machines acquired in step S718 are summed up for each item, and the respective total values are stored in the generated record. As a result, the performance data of all the large-sized machines of the day are stored in the generated record newly generated in this routine. With the above processing, the data for the large amount of money addition machine is stored in the generated record, so the same processing is performed for other terminal devices.

At step S720, all issuing machine numbers are acquired from the issuing machine connection file. This is the issuing machine of the hall (card issuing machine 2 in order to obtain the performance data of all issuing machines.
3) is specified. Then, step S722.
At the same time, the same-day data of all issuing machines are acquired from the issuing machine result file, the data of all the issuing machines acquired at step S724 are summed up for each item, and the respective total values are stored in the generated record. As a result, the performance data of all the issuing machines on the day is stored in the generated record newly generated in this routine. Since the data about the card issuing machine is stored in the generated record by the above processing, the same processing is performed for other terminal devices next. In step S726, all update machine numbers are acquired from the update machine connection file. this is,
In order to obtain the performance data of all update machines, the update machine of the hall (card update machine 24) is specified. Then
In step S728, the current day data of all the update machines are acquired from the update machine result file, the data of all the update machines acquired in step S730 are totaled for each item, and the respective total values are stored in the generated record. As a result, the result data of all the update machines of the day are stored in the generated record newly generated in this routine. Through the above processing, the data regarding the card update machine is stored in the generated record.
Next, in step S732, the data of the hole day result file is stored in the generated record. As a result, the performance data of the hole on the day is stored in the generated record newly generated in this routine. Next, in step S734, the generated record is added to the hole score file. In this way, all the today's scores for the hole are added as a new generated record, and the hole score file is updated.

I-9. Next Business Day Visiting Person Prediction Process FIG. 89 is a flowchart showing a subroutine of next business day visiting person prediction processing in the aggregation processing 1. In the next business day visitor number prediction process, first, in step S740, the visitor number data for the past three years is acquired from the hall result file, and the visitor number g of the business day average (that is, the average visitor number for one day) (a specific example will be described later). ) Is calculated. This is to refer to the past performance data of the hole in order to predict the number of people visiting the store on the next business day. Next, in step S742, it is determined whether or not there is data on the number of people visiting the store for the past three years. If not, the number of people visiting the store is acquired from the virtual hall result file and used in step S744. This is because, for example, when opening a new store or when it has not been in business for three years since the new store opened, there is no data on the number of people visiting the store, so a CD-RO provided by the gaming machine manufacturer.
The data of the hall result virtual file read from M is used. After step S744, the process proceeds to step S746.

If there is data on the number of people visiting the store for the past three years in step S742, the process jumps to step S744 and proceeds to step S746. In step S746, the monthly store index is calculated for each month. In this case, the average number of business days visiting the store for each month for the past three years is calculated, and the ratio between the calculated value (average number of business days visiting the store for each month) and the average number of business days visiting the store g is calculated as the monthly store index a [1]. ~ A [12]. Next, in step S748, a multiple-day store visit index is calculated for each of multiple days. In this case, the average number of business days visiting the store for each group of multiple days in the past three years is calculated, and the ratio of each obtained value (the average number of business days visiting the store for each group) and the average number of business days visiting the store g is calculated for multiple days. Store visit index b [1] -b
It is defined as [10]. As described above, the "plurality of days" is a group of dates that is approximately every 3 days.

Next, in step S750, a day-of-the-week visit index is calculated for each day of the week. In this case, the average number of business days visiting the store for each day of the past three years is calculated, and the ratio between the calculated value (average number of business days visiting the store for each day of the week) and the average number of business days visiting the store g is calculated as the day-of-week store index c [ 1] to c [7]. However, on holidays, year-end and New Year holidays, Bon holidays, etc.
The business day average number of people visiting the store is calculated as c [8], excluding the calculation targets of [1] to c [7]. Next, in step S752, the weather store index w is calculated for each weather. In this case, the average number of business days visiting the store for each weather for the past three years is calculated, and the ratio of each value (average number of business days visiting the store for each weather) and the average number of business days visiting the store g is calculated as the weather visiting index d.
It is defined as [1] to c [n]. The weather is, for example, fine, rain,
The number of distinctions corresponds to n, such as cloudiness and snow.

Next, in step S754, the ideal number R of people visiting the store on the day is calculated from the average number of customers visiting the store for the past three years, the monthly store index, the multiple-day store index, and the day-of-week store index. A specific method for calculating the ideal number of people visiting the store will be described in detail in an example described later. Next, in step S756, the number of people visiting the store on the day is acquired from the hall result file, and this is set as the actual number of people visiting the store E. Next, in step S758, the ratio of the actually-visited store visitor number E to the ideal store visitor number R is calculated, and this is stored in the hall result file as the popularity index data p of the day. Next, in step S760, the popularity index data for the last 30 business days counted from the current day is acquired from the hole result file, and the popularity index data for the next business day is estimated from the popularity index data acquired in step S762. This is based on past data so that it does not deviate significantly from the actual number of people visiting the store. Based on popularity index data for the past 30 business days including today, for example, the least-squares method, the popularity of the next business day The index p [1] is calculated.

Next, in step S764, it is determined whether or not the weather consideration flag is set, and if it is set, the process proceeds to step S766 to obtain the forecast weather data from the hall performance forecast file, and the corresponding weather visit index w
Is the weather visit index w for the next business day. Then, in step S768, the average number of customers visiting the business day for the past three years, the monthly visit index, the multiple-day visit index, the day-of-week visit index,
The ideal visitor number R of the next business day is calculated from the weather visit index. Then, it progresses to step S772. On the other hand, if the weather consideration flag is not set in step S764,
The process branches to step S770, the average number of business visits during the past three years, the monthly visit index for the next business day, the multiple-day visit index,
The ideal visitor number R of the next business day is calculated from the day-of-the-week visit index. That is, in this case, the ideal visitor number R of the next business day is calculated excluding the weather visit index. afterwards,
It proceeds to step S772. In step S772, a value obtained by multiplying the ideal number of people coming to the store R on the next business day by the estimated popularity index p of the next business day is stored in the hall performance prediction file as the number of people visiting the store on the next business day. In this way, the number of people visiting the store on the next business day is predicted.

[Specific Example of Prediction of Number of Customer Visits] Next,
A specific example of the prediction of the number of customers visiting the store, which is calculated in the routine of the process for estimating the number of customers visiting the store on the next business day, will be described in detail. (1) First, check the number of visitors to the business day for the past three years,
Business day average (that is, average number of people visiting the store per day) g
Is calculated. For example, assuming that today is July 7, 1995, the number of customers visiting the business day for the past three years is as follows. July 7, 1992 3520 people July 8, 1992 1345 people July 9, 1992 2438 people ... (Continued for 3 years thereafter) ... July 6, 1995 3210 people 3 years total 2,193,172. Since the number of business days is 951, the average number of people visiting the store on business days g is calculated by the following formula. g = 2193172 (person) ÷ 951 (day) = 2306 (person / day)

(2) Next, the monthly store visit index is calculated for each month. The monthly average number of business visits to the store for each of the past three years is calculated, and the ratio between the calculated value and the average number of business visits to the business day g is defined as monthly store indexes a [1] to a [12]. For example, looking at the number of people visiting the store in January over the past three years, the results are as follows. January 1993 45500 business days 25 days January 1994 54600 business days 26 days January 1995 48100 people Business days 25 days 3 years total 148200 people. Since the total number of business days in January is 76 days, the average number of people visiting the business day in January is calculated by the following formula. January business day average visitor number = 148200 (people) ÷ 76 (days) = 1950 (people / day)

Similarly, when the average number of people visiting the business day in February to December is obtained, the following is obtained in each month. January = 1950 (people / day) February = 2035 (people / day) March = 2314 (people / day) ... December = 1855 (people / day) By dividing by, the monthly store index a [1] to a [12] is obtained, and is as follows. January 1950/2306 = 0.846 = a [1] February 2035/2306 = 0.882 = a [2] March 2314/2306 = 1.003 = a [3] ... ... Dec 1855/2306 = 0.804 = a [12]

(3) Next, a multi-day store visit index is calculated for each of a plurality of days. The average number of business days visiting the store for each group of multiple days in the past three years is calculated, and the ratio of each value and the average number of business days visiting the store g is calculated as a multiple day store index b [1] to b.
[10]. “Multiple days” is defined as groups of dates, roughly every 3 days, according to the following principles. Group 1 1st to 3rd of every month Group 2 4th to 6th of every month Group 3 7th to 10th of every month ・ ・ ・ ・ ・ ・ Group 9 25th to 27th of every month Group 10 28th to 31st of every month

Now, for example, when checking the number of people visiting the group 1 in the past 3 years, the results are as follows. August 1, 1992 Number of people visiting the store 2456 people August 2, 1992 Number of customers visiting the store 3003 people August 3, 1992 Number of people visiting the store 2560 people September 1, 1992 Number of people visiting the store 2381 people September 2, 1992 Number of people visiting the store 2839 people・ ・ ・ ・ ・ ・ ・ ・ July 2, 1995 Number of people visiting the store 2722 people July 3, 1995 Number of people visiting the store 2488 people Total number of people visiting Group 1 for three years is 230311 people. Since the total number of business days of group 1 is 108 days, the average number of people visiting the business day of group 1 is calculated by the following formula. Group 1 business day average number of visitors = 230311 (people) ÷ 108 (days) = 2132 (people / day)

In the same manner, the average number of customers visiting the business day of the groups 2 to 10 is calculated and arranged from the group 1 and shown as follows. Group 1 business day average visitor number = 2132 (person / day) Group 2 business day average visitor number = 2530 (person / day) ... Group 10 business day average visitor number = 2933 (person / day)
(Day) By dividing these by the average number of customers visiting the store on business days g, the multi-day visiting index b [1] to b [10] is obtained,
It looks like this: Group 1 2132/2306 = 0.925 = b [1] Group 2 2530/2306 = 1.097 = b [2] Group 3 2449/2306 = 1.062 = b [3] 2933/2306 = 1.272 = b [10]

(4) Next, the day-of-week visit index is calculated for each day of the week. Average business day visitor numbers by day of the week for the past three years are calculated, and the ratio of the calculated value to the business day average visitor number g is defined as day-of-week store visit indexes c [1] to c [7]. However,
Holidays, year-end and New Year holidays, Bon holidays, etc. are excluded from the calculation, and the average number of people visiting these business days is calculated as c [8]. The following dates are "holidays" that are subject to c [8]. January 1-January 4 August 13-August 16 December 30-December 31 National holidays For example, the total number of people visiting on Sunday for the past 3 years excluding the above "holidays" When calculated, it became as follows. Sunday total number of visitors 402436 people Business days 150 days

When the average number of people visiting the store on Sunday is calculated, the calculation is performed as follows. Sunday business day average visitor number = 402436 (person) / 150 (day) = 2682 (person / day) Similarly, the business day average visitor number from Monday to Saturday is calculated as follows. Monday 1978 (person / day) Tuesday 1837 (person / day) Wednesday 2104 (person / day) ... Saturday 2535 (person / day)

[0224] The average number of people visiting the store on "holiday" was calculated to be 2756 (person / day). By dividing each of these values by the business day average visitor number g (g = 2306), the day-of-the-week visit indexes c [1] to c [7] are obtained and are as follows. Sunday 2682/2306 = 1.163 = c [1] Monday 1978/2306 = 0.858 = c [2] Tuesday 1837/2306 = 0.977 = c [3] ... Saturday 2535/2306 = 1 0.099 = c [7] “holiday” 2756/2306 = 1.195 = c [8]

(5) Next, the popularity index p is calculated. The actual number E of people actually visiting the store and the ideal number R of stores visiting today are obtained, and the ratio is defined as a popularity index p. The actually measured number E of visitors here means the number of gamers who actually visited the store today. Further, the ideal number R of people visiting the store is a numerical value obtained according to the following rules. (5-1) Method for calculating ideal number of people R to visit the store The following data was calculated according to the procedures (1) to (4) above. Average number of people visiting the store during the last three years g Monthly store index a [1] -a [12] Multiple-day store index b [1] -b [10] Day-of-week store index c [1] -c [8] Ideal store visitor number R is obtained by multiplying the above numerical values. For example, if today's date is Friday, July 7, 1995, the corresponding monthly visit index, multiple-day visit index, and day-of-week visit index are as follows.

Since it is July, the corresponding monthly store index = a
[7] Since it belongs to group 3 because it is 7 days, the corresponding multiple-day store visit index = b [3] Friday, and since it is not a “holiday” defined in (4) above, the corresponding day-of-week store visit index =
c [6]. The ideal number of people visiting the store is calculated by multiplying these three indexes by the average number of people visiting the store during the last three years, g.
Ask for. Therefore, today, we will calculate by multiplying the above numerical values. For example, the ideal number R of people visiting the store today on Friday, July 7, is as follows. Ideal number of people visiting the store R = g × a [7] × b [3] × c [6] = 2306 × 1.103 × 1.062 × 0.914 = 2469 (5-2) Calculation of popularity index p The popularity index p is calculated using the ideal number R of people visiting the store. Assuming that the actual number E of visitors to the store on Friday, July 7, today is 2245, the popularity index p is calculated as follows. Popularity index p = E / R = 2245/2469 = 0.909

(6) Next, the popularity index p of the next business day
[1] is calculated. The popularity index p [1] of the next business day is calculated using the popularity index of the last 30 business days including today. The popularity index before yesterday shall be calculated before yesterday. These popularity indexes are p [-29] -p
It is represented by [0]. For example, if today is July 7 and the previous popularity index is calculated, the result is as follows. Popularity index on June 4th 1.023 = p [-29] Popularity index on June 5th 1.135 = p [-28] Holidays on June 6th Popularity index on June 7th 0.934 = p [-27] ····· July 6 popularity index 0.822 = p [−1] July 7 popularity index 0.909 = p [0] Using these values, next time Business day popularity index p [1]
Is obtained by the method of least squares as shown in FIG. 90,
It is the predicted value (marked with X) in the figure.

(7) Next, the number of people visiting the store on the next business day is predicted. Popularity index p for the next business day obtained in (6) above
[1], average number of people visiting the store during the last three years g, monthly store index a [i], multiple-day store index b [j], day-of-week store index c
Predict the number of people visiting the store on the next business day using [k]. For example, the number of people visiting the store is predicted assuming that today is July 7 and the next business day is July 8. The prediction method applies the procedure of (5),
It is performed by obtaining the ideal number R of customers on July 8 and then multiplying by the predicted popularity index p [1]. According to this method, the number E ′ of visitors to the store on the next business day is predicted as follows. Considering each coefficient, which is a calculation element of the popularity index p [1], the estimated number of customers visiting the store on the next business day E ′ = R × p [1] is as follows. Since it is July, the corresponding monthly store index is a [7]. Since it is 8 days, since it belongs to group 3, the corresponding multiple-day store visit index is b [3]. Since it is Saturday and is not a “holiday” defined in (4), the corresponding day-of-the-week visit index = c [7].

Therefore, the ideal number R of people visiting the store today on Saturday, July 8 (corresponding to the next business day) is calculated by the following formula. R = g × a [7] × b [3] × c [7] = 2306 × 1.103 × 1.062 × 1.099 = 2968 Here, the predicted popularity index obtained in the above (6) is p [ 1] =
If it is 0.842, ideal visitor number R on July 8th
By multiplying the estimated popularity index p [1] by the estimated popularity index p [1], the estimated number E ′ of people visiting the store on the next business day is calculated as follows. Number of people coming to the store on the next business day E ′ = R × p [1] = 2968 × 0.842 = 2499 This number becomes the predicted number of people coming to the store E ′ on the next business day E ′.

I-10. Next Business Day Hole Operation Number Prediction Process FIG. 91 is a flowchart showing a subroutine of the next business day hole operation number prediction process in the aggregation process 1. In the next business day hall operation number prediction process, first, step S7.
At 80, the predicted number of people visiting the store is acquired from the hall result prediction file. Next, in step S782, the average number of people coming to the store for the number of hall-out balls in the past month is calculated based on the hole result file. This is to calculate the average number of out balls per person from the actual data of the number of people visiting the store. Then, the average value (average number of out balls per person) calculated in step S784 is multiplied by the predicted number of people visiting the store to obtain the hole predicted out number of balls. Next, in step S786, the hole prediction out ball number is stored in the hole prediction result file. The hole predicted out ball number here is used as a parameter for predicting the operation rate of the hole in consideration of the fact that it takes, for example, 0.6 seconds from the ball firing to generate an out ball. After step S786, the process returns to the totalization process 1.

I-11. FIG. 92 is a flowchart showing a subroutine of the next business day operation count prediction processing in the aggregation processing 1. In the next business day operation number prediction process, first, step S800.
The data for 14 business days in the past (particularly, the number of out balls) is acquired from the hall result file and the model result file. This is because the data for two weeks is averaged. Next, the operating occupancy ratio for each business day is calculated from the data acquired in step S802. The occupancy ratio is calculated by obtaining the ratio of the total number of out balls for the past 14 days and the number of out balls for each model. Then, step S
Using the operation occupancy ratio calculated in 804, the predicted operation occupancy ratio for the next business day is calculated for each model. This is obtained by using, for example, the least square method. Next, in step S806, the total of the estimated operation occupancy ratios of all models is corrected to "1".

Next, in step S808, the number of holes predicted out balls is acquired from the hole performance prediction file, and a value obtained by multiplying this by the operation occupancy ratio is taken as the model predicted out balls number. That is, the predicted operation occupancy ratio and the hole predicted out ball number obtained for each model are integrated to calculate the predicted out ball number for each model. Next, in step S810, a value obtained by dividing the model predicted out ball number by the number of P machines to which it belongs is set as the P machine predicted out ball number. As a result, the predicted number of out-balls per vehicle is obtained. Next, in step S812, the predicted number of P machine out balls of all P machines is stored in the P machine result prediction file. After step S812, the process returns to the totalization process 1. The predicted number of people visiting the store, the predicted number of out-balls, and the predicted number of out-balls for each gaming machine serve as basic data for predicting the sales and profit of the entire hall.

J. Post-Closing Business Processing FIG. 93 is a flowchart showing a subroutine of post-closing business processing in the data collection process. In the post-closing business processing, first, in step S820, the hall operating status of the hall day result file is set to "post-closing business". As a result, the hall operation status data changes from "checking for closing" to "business after closing". Next, in step S822, hole operating state data is acquired from the hole day result file. In this case, the data “business after closing” is acquired. Next, in step S824, it is determined whether the acquired data is "base adjustment". The “stand adjustment” means a state in which adjustment work such as setting of each stand becomes possible after the store is closed.
If it is not "base adjustment", the process stands by in step S824, and if it is "base adjustment", the post-closing business process is terminated and the process returns to the data collection process. As a result, the process moves to the platform adjustment transfer process 1 of the data collection process.

K. Platform Adjustment Data Transfer Process FIG. 94 is a flowchart showing a subroutine of the platform adjustment data transfer process in the data collection process. In the platform adjustment data transfer process, first, in step S830, the platform adjustment item selected from the platform adjustment item file is acquired. As shown in FIG. 51, the platform adjustment item file predetermines the adjustment items when performing platform (P machine) adjustment (for example, nail adjustment, jackpot probability setting change, etc.) in preparation for the next business when the hall is closed. Stored as a table adjustment item record. Therefore, in step S830, the platform adjustment item record is acquired. Next, in step S832, platform adjustment data file creation processing is performed (details will be described later in a subroutine).

The table adjustment data file is, as shown in FIG. 52, the table adjustment when the table (P machine) is adjusted (for example, nail adjustment, jackpot probability setting change, etc.) in preparation for the next business when the hall is closed. Data (that is, adjustment content) is stored as a platform adjustment data record. Therefore, in step S832, the adjustment content is set for all units. Next, in step S834, a platform adjustment packet is created from the platform adjustment data file. This is because the platform adjustment data is put on a packet and transmitted to each platform. Next, in step S836, a platform adjustment packet is transmitted to all P machines. As a result, the display units 7 of all P machines are
The platform adjustment data will be displayed on the screen of No. 4. After step S836, the process returns to the data collection process.

K-1. Platform Adjustment Data File Creation Process FIG. 95 is a flowchart showing a subroutine of the platform adjustment data file creation process in the platform adjustment data transfer process. In the platform adjustment data file creation process, first, in step S840, the platform number is acquired from the model layout file. This is because the pedestals of the halls are sequentially specified. It should be noted that the machine numbers of the P machines are first acquired from the number of a certain machine, and finally, the numbers of all the machines that are installed and operable in the hall are acquired. Next, in step S842, the unit number of the P machine and the unit numbers of the P machines located on the left and right of the P machine are stored in the machine adjustment data file. In step S842, the P machine and the P machines on both sides of the machine also simultaneously acquire the machine numbers, for the purpose of also referring to the machine adjustment data on both sides.

Item data of the selected item is stored in the platform adjustment data file in step S844. The item data is code information corresponding to the contents of items for adjusting the table (for example, nail adjustment, setting change of jackpot probability, etc.). This is to extract the contents of the selected item as the platform adjustment data. Next, in step S846, the data of the selected item of the previous business day and the current day of the machine are calculated from the data of the machine performance file of P and stored in the machine adjustment data file. This is because the previous result item data (previous result data) and the present day result item data (result data of the current day) are taken out. Next, step S8
At 48, the data of the selection items of the left stand and the right stand of the same day are calculated from the data of the P machine result file and stored in the stand adjustment data file. This is to retrieve the same-day result item data (result data of the current day) for the left and right pedestals.

Next, in step S850, the predicted data of the selection items of the current day and the next business day of the relevant machine is calculated from the data of the P machine result prediction file and stored in the machine adjustment data file. This is for extracting the present day setting item data (previously predicted data) and the present next business day setting item data (that is, the present forecasting data for the next business). Next, in step S852, the model number corresponding to the platform is acquired from the model layout file. This is to identify the model of the machine. Next, in step S854, the vehicle average data of the selection items of the model (that is, the average result data of the model on that day) is calculated from the data of the model result file and stored in the vehicle adjustment data file. This is for displaying the model average data on the screen of the display unit 74 and for reference of the stand adjustment.

Next, in step S856, the unit number of the next unit is acquired from the model layout file. This is to shift to the processing of the next table. Here, the unit numbers of the units online are sequentially acquired. Next, in step S858, it is determined whether or not the machine adjustment data file processing has been completed for all P machines. Since only one machine has been completed in the first routine, the process branches to NO and returns to step S842 to execute the same loop. repeat. When the platform adjustment data file process is completed for all P machines, the process returns from step S858 to YES to terminate this routine and returns to the platform adjustment data transfer process.

L. Aggregation Processing 2 FIG. 96 is a flowchart showing a subroutine of aggregation processing 2 in the data collection process. In the totaling process 2, first, in step S860, the hole operating state data in the hole day result file is set to "total 2". Next, in steps S862 to S876, a predetermined file update process is performed (the details will be described later in subroutines). That is, in step S862, automatic setting file creation processing, step S864 P machine time series result file update processing, step S866 model time series result file update processing, step S868 POS time series result file update processing, step S870 large machine time series result File update processing, S872 hall time series result file update processing, S
At 874, the hall score prediction file update process is performed, and at S876, the hall time series score prediction file update process is performed.

Next, in step S878, a game file update process is performed. Although the game file is not shown in the figure, when a game is played on a P machine, data that allows the situation to be stored is stored as a game record regardless of whether the game is played on a stand or a card basis. As a result, for example, the card usage status of each machine can be known, and the gaming status of each machine can be known for each card. The game record is collected once when the store is closed, and is fetched from the P machine basic file. As data of the game record, for example, a date, a card number, a machine number, a game ball rental usage amount, a game savings ball usage amount, a game playing time, a game out ball number, and a game safe ball number are set. By updating the game file, today's data for each pedestal and each card is totaled for all pedestals.

Next, in step S880, a visiting file update process is performed. Although not shown in the figure, the store visit file stores data as a store visit record capable of grasping the situation when the customer comes to the store (what kind of game the customer has with the card per day). As a result, it is possible to trace the trajectory of what kind of game the customer has visited and played. The store visit record is collected by importing and processing the data of the unit-to-unit addition history file, the amount-addition history file, and the settlement history file. As the data of the store visit record, for example, date, card number,
The time of coming to the store, the game time at the time of coming to the store, the number of premium added balls at the time of coming to the store, the amount of money added at the time of coming to the store, the amount of money rented at the time of coming to the store, the amount of money used at the time of coming to the store, the amount of money paid at the time of coming to the store, the amount of coins paid at the time of coming to the store are set.
By updating the store visit file, the status (including all the games, settlements, etc.) of the cards used on the day of the hall is created in the generated record, and the data of all the cards are sequentially stored in the store visit file. At this time, the visit record time, the ball rental sales amount (ball rental usage amount), the accumulated ball sales amount (saved ball usage amount), the number of out balls x 0.6 seconds (game time), are entered in the generated record. .

Next, in step S882, customer result file update processing (1) is performed. Figure 44 for the customer record file
As shown in, the game performance data when the customer visits the store is stored as a customer performance record. By performing the customer result file update process (1), the customer result record for the customer who used the card on the day of the hall is confirmed, and in the case of a new customer, the customer result record is additionally created. Next, in step S884, a customer result file update process (2) is performed. The customer record record of the customer record file is updated by fetching and processing the data of the store visit file when the store is closed. By performing the customer result file update process (2), for the customer who has visited the hall so far, all the result data of the customer is acquired and the content of the customer result record is updated. In addition, in the case of a new customer, a customer record record is created with the data at the time of this store visit and is added to the customer record file. After step S884, the process returns to the data collection process.

Next, in L-1 to L-8, each of the above-mentioned subroutines of the aggregation processing 2 will be described in detail. L-1. Automatic Setting File Creation Process FIG. 97 is a flowchart showing a subroutine of the automatic setting file creation process in the aggregation process 2. As shown in FIG. 21, the automatic setting file stores the machine number and the game setting value as an automatic setting record for each machine. In order to transfer the game setting value from the management device 11 to each machine when the store is closed. , When the business is closed, the automatic setting file is updated to prepare for the next business. In the automatic setting file creation processing, first, in step S890, the unit number is acquired from the model layout file. This is to identify the pedestals of the hall in sequence.

Next, in step S892, an automatic setting record is generated. This is to add the automatic setting record of the P machine because the game setting value for the next business of the P machine is added when the store is closed. Next, in step S894, the machine number is stored in the generated record, and in step S896, the scheduled game setting value of the machine number is acquired from the P machine result prediction file. Next, the game setting value acquired in step S898 is stored in the generated record. As a result, the scheduled game setting value for the next business day of the P machine is stored in the generated record newly generated in this routine. Next, in step S900, the generated record is added to the automatic setting file. As a result, the scheduled game setting value of the next business day of the P machine is added as a record to the automatic setting file of the P machine. Next, in step S902, the next unit number is acquired from the model layout file. This is to move to the next machine since the update of the automatic setting file of the P machine is completed. Next, in step S904, it is determined whether or not all of the units have ended. Since only one unit has ended in the first routine, the process branches to NO and returns to step S892 to repeat the same loop.

When the processing of all the units is completed, the determination result of step S904 is YES and step S90
Proceed to 6. In step S906, the updated automatic setting file is moved to the storage device of the management apparatus 11. As a result, the contents of the automatic setting file are transferred from the management device 11 to each device in a predetermined packet (the contents of this file are sent to the corresponding terminal devices as initial values). After step S906, the process returns to the totaling process 2. In this way, the scheduled game setting value for the next business day is added as a new generation record for all the halls, and is transmitted from the management device 11 to each hall.

L-2. P Machine Time Series Result File Update Process FIG. 98 is a flowchart showing a subroutine of the P machine time series result file update process in the aggregation process 2. P
As shown in FIG. 27, the machine time-series result file includes data indicating the performance of each machine (cumulative value data from the opening of the hall) for each machine and in time series (every 5 minutes). Is stored as, and is used as data for prediction for the next business calculated when the business is closed. In the P machine time series result file update processing, first, in step S910, the machine number is acquired from the model layout file. This is to identify the pedestals of the hall in sequence. Next, in step S912, the basic file of the P machine is selected. As shown in FIG. 25, the P machine basic file stores the result data of the P machine as a P machine basic record for each machine and each business day, and is stored in the external storage device.

Next, in step S914, the oldest division time is acquired from the time-series unit time file. This is to get the time in the first 5 minutes since the start of business today. For example, if the store opens at 10 am, then 10 am
Five minutes is the oldest division time. Then, step S91
At 6, the P machine time series result record is generated. This is to add the time series result record of the P machine because the data of today to be added to the time series result file of the P machine when the store is closed is added as a record. Next, in step S918, the division time, the date of the current day, and the machine number of the P machine are stored in the generated record. This is to specify the time series data to be stored in this routine. Then
In step S920, a record of "time = division time" and "event code = constant time" is acquired from the selected P machine basic file. Then, step S922.
Store each data value of the acquired record in the generated record. As a result, it becomes clear that the data is time-series data at a fixed time every 5 minutes. Next, in step S924, the generated record is added to the P machine time series result file. As a result, the oldest fixed time of the P machine (for example, 10:00
The time series data of 5 minutes) is stored in the generated record, and the P machine time series result file is updated.

Next, in step S926, the next division time is acquired from the time-series unit time file. For example, in the first loop, since the first five-minute increments have been obtained since the start of business today, the next loop is to obtain 10:10. Next, in step S928, it is determined whether or not the next division time exists. In other words, this is to determine whether or not all the division times until the store is closed have been acquired. In the first loop, the next division time is 10:10, which is not when the store is closed. Therefore, the flow branches to NO to return to step S916, and the same loop is repeated. Then, when the processing for all the division times until closing is completed,
The determination result of step S928 is YES, and the process proceeds to step S930. As a result, the update of the time-series result file is completed for the first P machine with the machine number acquired first.

In step S930, the next unit number is acquired from the model layout file. This is to move to the next machine because the time series result file of the P machine has been updated. Next, in step S932, it is determined whether or not all the units have ended. Since only one unit has ended in the first routine, the process branches to NO in step S912.
Return to and repeat the same loop. And processing of all units is completed (update of time series accumulated data for all units of today is completed)
Then, the determination result of step S932 becomes YES, and the process returns to the totaling process 2. In this way, the P machine time-series result files are updated for all machines, information for every 5 minutes such as sales amount, number of out balls, number of safe balls, etc. for each gaming machine is calculated, and the external storage device 157 is calculated. Stored in.

L-3. Model Time Series Result File Update Processing FIG. 99 is a flowchart showing a subroutine of model time series result file update processing in the aggregation processing 2. As shown in FIG. 29, the model time-series result file stores data indicating the results of each model as a model time-series result record for each model and in chronological order. It is used as data for forecasting. In the model time-series result file update process, first, in step S940, the model number is acquired from the model information file. This is because the models are sequentially specified. Next, in step S942, the oldest division time is acquired from the time-series unit time file. Similarly, this is to obtain the first time every 5 minutes from the start of business. For example, if the opening time is 10 am, 10:05 is the oldest division time. Next, in step S944, a model time series performance record is generated. This is to add the time-series result record of the model because the data of today to be added to the time-series result file of the model when the store is closed is added as a record.

Next, in step S946, the division time, the date of the current day, and the model number of the model are stored in the generated record. This is to specify the time series data to be stored in this routine. Next, in step S948, the machine numbers of all P machines belonging to the model are acquired from the model layout file. Since this updates the model time-series result file, it identifies all units of the same model.
Next, from the P machine time series result file of the model acquired in step S950, the data of all the P machines belonging to the model, which is the current day and "time = division time", is acquired. Then, in step S952, all Ps belonging to the model are
Machine data is summed up for each item, and the total value of each is stored in the generated record. As a result, the time-series data of all P machines at a fixed time every 5 minutes is stored in the generated record item by item. Next, in step S954, the generated record is added to the model time series result file. This allows
The time series data of the oldest fixed time (for example, 10:05) of the model is stored in the generated record, and the model time series result file is updated.

Next, in step S956, the next division time is acquired from the time-series unit time file. For example, in the first loop, since the first five-minute increments have been obtained since the start of business today, the next loop is to obtain 10:10. Next, in step S958, it is determined whether or not the next division time exists. In other words, this is to determine whether or not all the division times until the store is closed have been acquired. In the first loop, the next divided time is 10:10, which is not the time of closing the store, so the flow branches to NO and returns to step S944 to repeat the same loop. Then, when the processing for all the division times until closing is completed,
The determination result of step S958 becomes YES, and the process proceeds to step S960. As a result, the update of the time series result file is completed for the models in one group corresponding to the model number acquired first.

In step S960, the next model number is acquired from the model information file. This is to move to the next model because the time series result file of the model has been updated. Next, in step S962, it is determined whether or not all models have ended. Since only one model has ended in the first routine, the process branches to NO in step S962.
Returning to 942, the same loop is repeated. Then, when the processing of all models ends (update of the time-series cumulative data of all models for today ends), the determination result of step S962 is YE.
The process returns to S and returns to the counting process 2. In this way, the model time-series result files for all models are updated, and the sales amount, out ball number, safe ball number, etc. for each model are updated.
Information for each minute is calculated and stored in the external storage device 157.

L-4. POS Time-series Result File Update Processing FIG. 100 is a flowchart showing a subroutine of the POS time-series result file update processing in the aggregation processing 2. As shown in FIG. 34, the POS time series result file is
Data showing the performance of each free gift POS 14 is stored as a POS time series performance record for each free gift POS and in chronological order, and is used as data for forecasting prepared for the next business which is calculated when the business is closed. Is. In the POS time-series result file update processing, first, in step S970, the POS number is acquired from the POS connection file. This is because the POS (the prize POS 14, the same applies hereinafter) is sequentially specified. Next, in step S972, the first division time is acquired from the time-series unit time file. This is likewise to obtain the time in the first 5 minutes from the start of business, for example, if the opening time is 10 am, 10
Hour 05 is the first division time. Then, step S
At 974, a POS time series performance record is generated. This is to add the time-series result record of the POS because the data of the day to be added to the time-series result file of the POS at the time of closing the store is added as a record.

Next, in step S976, the division time, the date of the current day, and the POS number of the POS are stored in the generated record. This is to specify the time series data to be stored in this routine. Next, at step S978, the time <
What is the division time, that is, the one whose current time is earlier than the division time (the first division time in the first loop) is acquired. For example, when the division time = 10: 05, the record whose current time is less than 10:05 is acquired. This is because the data of the records before the division time is a cumulative value, so that the time series adjustment data can be obtained by acquiring the record contents before the division time. Next, the total sum of the redemption amount and the stored amount of the record acquired in step S980 is stored in the generated record. As a result, the time-series data of the POS at a fixed time every 5 minutes is stored in the generated record for each item (here, the amount of redemption and the amount of accumulated coins). Then
In step S982, the generated record is added to the POS time series result file. As a result, the time series data at the fixed time (for example, 10:05) at the head of the POS is stored in the generated record, and the POS time series result file is updated.

Next, in step S984, the next division time is acquired from the time-series unit time file. For example, in the first loop, since the first five-minute increments have been obtained since the start of business today, the next loop is to obtain 10:10. Next, in step S986, it is determined whether or not the next division time exists. In other words, this is to determine whether or not all the division times until the store is closed have been acquired. In the first loop, the next division time is 10:10, which is not when the store is closed. Therefore, the flow branches to NO to return to step S974, and the same loop is repeated. Then, when the processing for all the division times until closing is completed,
The determination result of step S986 is YES, and the process proceeds to step S988. As a result, the update of the POS time-series result file for one POS corresponding to the POS number acquired first is completed.

In step S988, the next POS number is acquired from the POS connection file. This is to move to the next POS since the update of the POS time-series result file of the POS has been completed. Then, step S99
When it is 0, it is determined whether or not all POSs have ended. Since only one POS has ended in the first routine, the process branches to NO and returns to step S972 to repeat the same loop. Then, processing of all POS ends (all POS of today
When the update of the POS time-series cumulative data is completed), the determination result of step S990 becomes YES and the process returns to the totaling process 2. In this way, PO for all POS
The S time-series result file is updated, information for every 5 minutes such as the amount of redemption for each POS, the amount of accumulated coins, etc. is calculated and stored in the external storage device 157.

L-5. Large Machine Time Series Result File Update Processing FIG. 101 is a flowchart showing a subroutine of large machine time series result file update processing in the aggregation processing 2. As shown in Fig. 35, the time series results file for large aircraft is
Data indicating the performance of each large-sized money adding machine 25 is stored as a large-sized machine time-series result record for each large-sized money adding machine in time series. It is used for the data of. In the large machine time series result file update process, first, step S
At 1000, the large machine number is acquired from the large machine connection file. This is because the large-sized machines (the large-sized money adding machines 25, the same applies hereinafter) are sequentially specified. Next, in step S1002, the first division time is acquired from the time-series unit time file. This is also to obtain the first time every 5 minutes from the start of business. For example, if the store opens at 10 am, 10:05 is the first division time. Next, in step S1004, a large machine time series result record is generated. This is to add the time-series result record of the large-sized machine because the data of today that is added to the time-series result file of the large-sized machine is added as a record when the store is closed.

Next, in step S1006, the division time, the date of the day, and the large machine number of the large machine are stored in the generated record. This is to specify the time series data to be stored in this routine. Then, step S100
In step 8, the record of the large-sized machine is obtained from the amount-addition history file, where time <division time, that is, the current time is earlier than the division time (the first division time in the first loop). For example, when the division time = 10: 05, the record whose current time is less than 10:05 is acquired. This is because, similarly, the data of the records before the division time is an accumulated value, and therefore the time series adjustment data can be obtained by acquiring the record contents before the division time. Then, step S1010.
The total value of the premium additional balls and the additional amount of the record acquired in step 1 is stored in the generated record. As a result, the time-series data of the large machine at a fixed time every 5 minutes is stored in the generated record for each item (here, the number of premium additional balls and the additional amount of money). Next, in step S1012, the generated record is added to the large machine time series result file. As a result, the time series data at the head fixed time (for example, 10:05) of the large machine is stored in the generated record, and the large machine time series result file is updated.

Next, in step S1014, the next division time is acquired from the time-series unit time file. For example, in the first loop, since the first five-minute increments have been obtained since the start of business today, the next loop is to obtain 10:10. Next, in step S1016, it is determined whether or not the next division time exists. In other words, this is to determine whether or not all the division times until the store is closed have been acquired. In the first loop, the next divided time is 10:10, which is not when the store is closed. Therefore, the flow branches to NO to return to step S1004, and the same loop is repeated. Then, when the processing for all the division times until the closing of the store is completed, the determination result of step S1016 becomes YES and the process proceeds to step S1018. As a result, the update of the large machine time series result file for one large machine corresponding to the first acquired large machine number is completed.

At step S1018, the next large machine number is acquired from the large machine connection file. This is to move to the next large machine because the update of the large machine time series result file of the large machine has been completed. Then, step S1
At 020, it is judged whether or not all the large-sized machines have ended. In the first routine, only one large-sized machine has ended, so N
It branches to O and returns to step S1002 to repeat the same loop. Then, when the processing of all the large-sized machines is completed (the update of the large-sized machine time-series cumulative data of all the large-sized machines of today is completed), the determination result of step S1020 becomes YES, and the process returns to the aggregation processing 2. In this way, the large machine time-series result file is updated for all large machines, the additional amount of money for each large amount of additional machine, the number of premium additional balls, etc. are calculated every 5 minutes, and the external storage device 157 is calculated. Stored in.

L-6. Hall Time-series Result File Update Processing FIG. 102 is a flowchart showing a subroutine of hole (current day) time-series result file update processing in the aggregation processing 2. As shown in FIG. 36, the hall time-series result file stores data indicating the results of the entire hall on the day in time series as a hall day-time series result record, and is prepared for the next business calculated when the business is closed. It is used for data for. In the hall time-series result file update process, first, in step S1030, the division time (particularly, the division time at the beginning) is acquired from the time-series unit time file. This is to get the time every 5 minutes from the start of business. For example, if the opening time is 10 am, it is 10:05.
The minute is the first division time. Then, step S103
In 2, generate a hole time series performance record. This is to add the time-series result record of the hole, because the data of today to be added to the time-series result file of the hole when the store is closed is added as a record.

Next, in step S1034, the division time and the date of the current day are stored in the generated record. This is to specify the time series data to be stored in this routine. Next, in step S1036, all model numbers are acquired from the model information file. This is to identify the hall model in order to obtain time-series performance data for all models. Next, in step S1038, the data of all models for the current day and “time = division time” are acquired from the model time-series result file, the data of all models acquired in step S1040 are totaled for each item, and each total value is generated. Store to. As a result, the time-series performance data of all the models on the day will be stored in the generated record newly generated in this routine. With the above processing, the time-series data for the gaming machine is stored in the generated record, so next, the same processing is performed for the terminal device.

That is, in step S1042, all POS numbers are acquired from the POS connection file. This is all P
To obtain OS time-series performance data, POS at the hall
The (prize POS 14) is specified. Next, in step S1044, all Ps are read from the POS time-series result file.
Acquire the data of the day of the OS and "time = division time",
The data of all POSs acquired in step S1046 are summed up for each item, and the respective summed values are stored in the generated record. As a result, the time-series performance data of all POSs on the current day are stored in the generated record newly generated in this routine. With the above processing, the time-series data for the prize POS 14 is stored in the generated record, so the same processing is performed for other terminal devices next. Step S
At 1048, all large machine numbers are acquired from the large machine connection file. This is to specify the large-sized machine (large-sized money addition machine 25) in the hall in order to obtain time-series performance data of all large-sized machines. Next, in step S1050, the data of all large machines on the same day and "time = division time" are acquired from the large machine time-series result file, and the data of all large machines acquired in step S1052 are totaled for each item, and the total value of each is obtained. Is stored in the generated record. As a result, the time-series performance data of all the large-sized machines of the day will be stored in the generated record newly generated in this routine. With the above processing, the data for the large amount of money addition machine is stored in the generated record, so the same processing is performed for the current date / time series result file of the hole.

In step S1054, the data of "time = division time" is stored in the generated record from the hole date / time series result file. As a result, the time-series performance data of the hall on that day is stored in the generated record newly generated in this routine. By the above processing, the time-series result data of the game machine, the prize POS 14, the large amount of money addition machine 25, and the hall of the day are stored in the generated record and become here. Next, in step S1056, the next division time is acquired from the time-series unit time file. For example, in the first loop, since the first five-minute increments have been obtained since the start of business today, the next loop is to obtain 10:10. Next, in step S1058, it is determined whether or not the next division time exists. In other words, this is to determine whether or not all the division times until the store is closed have been acquired. In the first loop, the next divided time is 10:10, which is not the time of closing the store. Therefore, the flow branches to NO to return to step S1032, and the same loop is repeated. And
When the process for all the division times until the closing of the store is completed, the determination result of step S1058 becomes YES and the process returns to the totaling process 2. In this way, the hall time series result file is updated, and the sales amount of the entire hall,
Information every 5 minutes such as the number of out balls, the number of safe balls, the amount of redemption, the amount of stored balls, the number of people visiting the store is calculated and stored in the external storage device 157.

L-7. Hall Result Prediction File Update Processing FIG. 103 is a flowchart showing a subroutine of hole result prediction file update processing in the aggregation processing 2.
As shown in FIG. 41, the hall performance prediction file stores data for predicting the performance of the entire hall (particularly, the performance of the next business day) as a hall performance prediction record. Updated with forecast data for. In the hall result prediction file update processing, first, in step S1060, the predicted number of people visiting the store (the predicted number of people visiting E on the next business day E ′, the same applies hereinafter) is acquired from the hall result prediction file. Then, step S106
In step 2, calculate the average number of visitors to the number of hall premium added balls for the past month based on the data in the hall result file. This is to calculate the average number of premium additional balls per person from the actual data of the number of people visiting the store. Next, a value obtained by multiplying the average value (average number of premium additional balls per person) calculated in step S1064 by the predicted number of people visiting the store is stored in the hole performance prediction file as the number of predicted premium additional balls. In this way, the prediction data of the number of premium additional balls is updated.

Next, in step S1066, the average number of people visiting the store for the number of bonus balls in the past month is calculated based on the data in the hole score file. This is to calculate the average number of bonus balls per person from the actual data of the number of people visiting the store. Next, a value obtained by multiplying the average value calculated in step S1068 (the average number of bonus balls per person) by the predicted number of people visiting the store is stored in the hall result prediction file as the number of hole bonus bonus balls. In this way, the prediction data of the number of bonus balls is updated. Then, step S1
At 070, based on the data of the hole result file, the ratio between the hole conversion amount and the hole accumulated amount for the past month is calculated.
This is to calculate the average redemption amount and redemption amount per person from the actual redemption amount data and the actual redemption amount data. Next, in step S1072, the hole forecast sales amount and the hole forecast expected profit are acquired from the hole result forecast file, and the amount of money to be settled at the POS (prize POS14) is calculated by adding the number of hole forecast premium added balls and the number of hole forecast bonus balls Predict. This is to get close to the regular profit by subtracting the bonus amount (predicted premium additional ball number, predicted bonus ball number) of the hole from the profit (hole predicted sales amount, expected hole profit).

Next, P predicted in step S1074
Multiply the settlement amount of the OS by the ratio of the amount converted / amount accumulated (amount converted / amount accumulated) calculated in step S1070,
These are the estimated hole conversion amount and the estimated hole accumulated amount, respectively.
This is to predict the redemption amount and the accumulated amount of coins with reference to the actual data of the holes. Then, step S10
In step 76, the calculated hole prediction conversion amount and the calculated hole prediction amount are stored in the hole result prediction file. In this way,
When the hall is closed, the data of the hall performance forecast file for the next business is updated based on the past performance data. After step S1076, the process returns to the totalization process 1.

L-8. Hall Time Series Results Prediction File Update Processing FIG. 104 is a flowchart showing a subroutine of hall time series results prediction file update processing in the aggregation processing 2. As shown in FIG. 42, the hall time-series performance prediction file stores, as a hall time-series performance prediction record, data for predicting the performance of the entire hall (especially, the performance of the next business day) in time series, which is set at the time of closing the store. The time series forecast data for the next business will be updated based on the above data.
In the hall time-series performance prediction file updating process, a process of creating a predetermined file is performed in each of steps S1080 to S1096 (the details will be described later in subroutines). That is, in step S1080, hall time-series predicted sales amount data creation processing, step S1082.
In step S1084, hole time-series predicted out ball number data creation processing, in step S1086, time-series predicted visitor number data creation processing, in step S1088, hall time-series predicted bonus ball number data creation Processing, hole time series prediction premium ball number data creation processing in step S1090, step S1
At 092, a hole time series forecast conversion amount data creation processing is performed, at step S1094 a hole time series forecast bet amount data creation processing is performed, and at step S1096 a hall time series forecast expected profit data creation processing is performed. When the process of creating each of the above files is completed in this way, the process returns to the totaling process 2.

Next, in L-8-1 to L-8-9,
Each of the above subroutines of the hall time-series performance prediction file update processing will be described in detail. L-8-1. Hall time-series result prediction sales amount data creation processing FIG. 105 is a flowchart showing a subroutine of hall time-series result prediction sales amount data creation processing in the hall time-series result prediction file update processing. In the hall time series performance prediction sales amount data creation processing, step S1100
Acquire the hall time-series sales amount data group from the hall time-series result file and use it as the input data A. The hall time-series sales amount data group is a set of time-series sales amount data for every 5 minutes.

Next, in step S1102, the hole sales amount data is acquired from the hole result file and used as the input data B. Next, in step S1104, the hole predicted sales amount data is acquired from the hole result file and set as the input data C. Next, in step S1106, time series prediction data creation processing is performed (details will be described later in a subroutine).
This is to create time-series predicted sales amount data on the next business day based on the input data A, B, and C, and use it as output data. Next, in step S1108, the output data is stored in the hall time-series forecast file as the hall time-series forecast sales amount. After step S1108, the process returns to the hall time-series performance prediction file update process. In this way, the hall time-series performance forecast sales amount data is created.

L-8-2. Hole Time Series Predicted Out Ball Number Data Creation Processing FIG. 106 is a flowchart showing a subroutine of hole time series predicted out ball number data creation processing in the hall time series result prediction file update processing. In the hole time series prediction out ball number data creation processing, step S1110
Then, the hole time-series out ball number data group is acquired from the hole time-series result file and used as the input data A. The hole time series out ball number data group is a set of time series out ball number data for every 5 minutes. Then, step S1112.
Then, the hole-out ball number data is acquired from the hole result file and used as the input data B. Then, step S111
In 4, the hole prediction out ball number data is acquired from the hole result file and used as the input data C. Then, step S
At 1116, time series prediction data creation processing is performed (details will be described later in a subroutine). This is to create time-series predicted out-ball-number data on the next business day based on the input data A, B, and C, and use it as output data. Next, in step S1118, the output data is stored in the hall time-series prediction file as the hole time-series prediction out ball number. After step S1118, the process returns to the hall time-series performance prediction file update process. In this way, the hole time series performance prediction out ball number data is created.

L-8-3. Hole Time Series Predicted Safe Ball Number Data Creation Processing FIG. 107 is a flowchart showing a subroutine of hole time series predicted safe ball number data creation processing in the hall time series result prediction file update processing. In the hole time series prediction safe ball number data creation processing, step S1120
Then, the hole time series safe ball number data group is acquired from the hole time series result file and used as the input data A. The hole time series safe ball number data group is a set of time series safe ball number data for every 5 minutes. Then, step S1122.
Then, the hole safe ball number data is acquired from the hole result file and is used as the input data B. Then, step S112
In 4, the hole prediction safe ball number data is acquired from the hole result file and is used as the input data C. Then, step S
At 1126, time series prediction data creation processing is performed (details will be described later in a subroutine). This is to create time-series predicted safe ball number data on the next business day based on the input data A, B, and C, and use it as output data. Next, in step S1128, the output data is stored in the hall time series prediction file as the number of holes time series prediction safe balls. After step S1128, the process returns to the hall time-series performance prediction file update process. In this way, the hole time series performance prediction safe ball number data is created.

L-8-4. Hall Time-series Predicted Number of People Visiting Stores Data Creation Process FIG. 108 is a flow chart showing a subroutine of a process of creating hall-time-series predicted number of customers visiting stores in the hall time-series result prediction file update process. In the hall time-series predicted visitor number data creation processing, a hall time-series visitor number data group is acquired from the hall time-series result file and is used as the input data A in step S1130. The hall time-series safe ball number visitor number group is a set of time-series visitor number data every 5 minutes. Next, in step S1132, the number of people visiting the store is acquired from the hall result file and set as the input data B. Next, in step S1134, the predicted number of people visiting the hall is acquired from the hall result file and set as the input data C. Next, in step S1136, time series prediction data creation processing is performed (details will be described later in a subroutine). This is to create time-series predicted visitor number data on the next business day based on the input data A, B, and C, and use it as output data. Next, in step S1138, the output data is stored in the hall time-series prediction file as the hall time-series prediction visitor number. After step S1138, the process returns to the hall time-series performance prediction file update process. In this way, the hall time-series performance prediction visitor number data is created.

L-8-5. Hole Time Series Predicted Bonus Ball Number Data Creation Processing FIG. 109 is a flowchart showing a subroutine of hole time series predicted bonus ball number data creation processing in the hall time series result prediction file update processing. In the hole time series prediction bonus ball number data creation processing, step S1140
Then, the group of time-series bonus ball number data is acquired from the hall time-series result file and used as input data A. The hole time series safe ball number bonus ball number group is a set of time series bonus ball number data for every 5 minutes. Next, step S11
At 42, the number-of-holes bonus data is acquired from the hole score file and is used as the input data B. Then, step S1
At 144, the hole prediction bonus ball number data is acquired from the hole result file and is used as the input data C. Next, in step S1146, time series prediction data creation processing is performed (details will be described later in a subroutine). This is the input data A, B,
Based on C, the time series forecast bonus ball number data of the next business day is created and used as output data. Next, in step S1148, the output data is stored in the hall time-series prediction file as the number of bonus balls for the time-series prediction of the hall. After step S1148, the process returns to the hall time-series performance prediction file update process. In this way, the hole time series performance prediction bonus ball number data is created.

L-8-6. Hole Time Series Predicted Premium Added Ball Number Data Creation Processing FIG. 110 is a flowchart showing a subroutine of hole time series predicted premium added ball number data creation processing in the hall time series performance prediction file update processing. In the hole time-series predicted premium additional ball number data creation processing, a hole time-series premium additional ball number data group is acquired from the hole time-series result file and used as input data A in step S1150. The hole time-series premium additional ball number data group is a set of time-series premium additional ball number data for every 5 minutes. Next, in step S1152, the number data of hole premium added balls is acquired from the hole result file and set as the input data B.

Next, in step S1154, the hole prediction premium additional ball number data is acquired from the hole result file and set as the input data C. Next, step S115
In step 6, time series prediction data creation processing is performed (details will be described later in a subroutine). This is to create time-series predicted premium additional ball number data on the next business day based on the input data A, B, and C, and use it as output data. Next, in step S1158, the output data is stored in the hall time-series prediction file as the number of hall time-series prediction premium added balls. After step S1158, the process returns to the hall time-series performance prediction file update process. In this way,
Hole time-series performance prediction Premium additional ball number data is created.

L-8-7. Hall Time-series Predicted Exchange Amount Data Creation Process FIG. 111 is a flowchart showing a subroutine of the hall time-series forecast exchanged amount data creation process in the hall time-series result forecast file update process. In the hole time-series predicted exchange amount data creation processing, a group of hall time-series exchange amount data is acquired from the hole time-series result file and is used as input data A in step S1160. The hall time-series exchange amount data group is a set of time-series exchange amount data for every 5 minutes. Next, in step S1162, the hole conversion amount data is acquired from the hole result file and set as the input data B. Next, in step S1164, the hole prediction conversion amount data is acquired from the hole result file and set as the input data C. Next, in step S1166, time series prediction data creation processing is performed (details will be described later in a subroutine). This is to generate time-series predicted exchange amount data on the next business day based on the input data A, B, and C, and use it as output data. Next, in step S1168, the output data is stored in the hall time series prediction file as the hall time series prediction conversion amount. After step S1168, the process returns to the hall time-series performance prediction file update process. In this way, the hall time-series performance prediction conversion amount data is created.

L-8-8. Hole Time-Series Predicted Savings Data Calculation Processing FIG. 112 is a flowchart showing a subroutine of hole-time-series predicted savings amount data creation processing in the hole time-series performance prediction file update processing. In the hole time-series predicted bet amount data creation processing, a hole time-series bet amount data group is acquired from the hole time-series result file and used as input data A in step S1170. The hole time-series amount of accumulated coin amount data is a set of time-series accumulated amount of coin data for every 5 minutes. Next, in step S1172, the amount-of-holes-collected-balls data is acquired from the results-of-holes file and used as input data B. Next, in step S1174, the hole predicted accumulated amount data is acquired from the hole result file and set as the input data C. Next, in step S1176, time series prediction data creation processing is performed (details will be described later in a subroutine). This is to generate time-series predicted amount-of-collected-balls data on the next business day based on the input data A, B, and C and use it as output data. Next, in step S1178, the output data is stored in the hall time-series prediction file as the hall time-series predicted ball storage amount. After step S1178, the process returns to the hall time-series performance prediction file update process. In this way, the hole time-series performance prediction accumulated amount data is created.

L-8-1-1. Time Series Prediction Data Creation Process FIG. 113 is a flowchart showing a subroutine of the time series prediction data creation process in the hall time series prediction sales amount data creation process and the like. In the time-series prediction data creation process, a specific example (a specific example is sales amount data, but the same applies to the accumulated coin amount data) will be described with reference to FIGS. 114 to 116. First, in step S1180, of the input data A and B for the past one year, the data for which the next business day and the day of the week match is targeted. That is, the time-series data group for every 5 minutes and the accumulated value data are searched from the past year's actual data, and the same data as the day of the next business day is extracted.
Next, in step S1182, time series data for any one day is designated from the data A. Then, step S
At 1184, the result data corresponding to the designated time series data (cumulative value data of the designated one day) is acquired from the data B.

Specifically, as shown in FIG. 114 (a),
Time-series sales amount data for every 5 minutes on an arbitrary day and final accumulated sales amount data (for example, 1 million yen) are acquired.
In the example of FIG. 114 (a), opening of a hall = 10: 00
Minutes, Closing = 22:00, which is an operating state, and time series data is acquired every 5 minutes during this period. Next, the designated time-series data is converted into 100-division unit data using the result data obtained in step S1186. As a result, the cumulative value is divided into 100 along the time series data. Converting to 100-division unit data is the same unit (100-division unit) because it is not possible to simply compare the time-series data of each day if business hours are different (such as when opening hours and closing times are different). To replace the data.

Here, the conversion process will be specifically described. First, as shown in FIG. 114 (b), the opening time of the hall is "0", the closing time is "100", and the interval is divided into 100, and the time-series sales amount data is divided according to the timing of 100 divisions. As a result, the time-series sales amount data becomes a set of 100 division points as shown in FIG. 114 (c). Next, as shown in FIG. 114 (d), the cumulative sales amount data (for example, 1 million yen) is replaced with "1", and the time-series sales amount data is divided (divided) by the cumulative sales amount data, respectively. It is sequentially replaced with a value less than "1". As a result, the value starts from "0" and the final value is "1".
Is converted into 100-division unit data that reaches (Fig. 11
4 (d) state). This means that regardless of whether the business hours are long or short, the time-series changes in the sales amount from the opening of the store to the closing of the store are uniformly set to the final value based on the accumulated sales amount data and the actual time-series sales amount data. 1 ”means that the data has been converted into 100-division unit data. This makes it possible to compare the changes in sales amount on each business day with the same scale.

Next, in step S1188, the next one day of time series data is designated from the data A. Then
In step S1190, it is determined whether or not the conversion of all the time-series data is completed. In the first loop, the conversion of only one day of time-series data is completed, so the process branches to NO and proceeds to step S1184. Return and repeat the same loop. Then, when the conversion of all the time-series data of the data A is completed, the determination result of step S1190 becomes YES, and the process advances to step S1192. This state is shown in FIG.
As shown in (e), the time series data of multiple business days is 10
It is converted into 0 division unit data, and is represented as a plurality of 100 division unit data (in the figure, drawn by a curve for easy viewing).

[0285] In step S1192, the average value of the 100-division unit data is calculated and used as the predicted 100-division unit data. As shown in FIG. 114 (f), this converts time series data of a plurality of business days into 100-division unit data,
It is represented as a state (state of predicted 100-division unit data) obtained by taking the average value thereof. Then, step S1
At 94, the predicted 100 division unit data is converted into the predicted time series unit data for the next business day. This is to convert data by replacing the prediction 100 division unit with a prediction time series unit every 5 minutes. First, as shown in FIG. 114 (g), the predicted 100-division unit data curve is divided into 100 and divided into a set of points.

On the other hand, as shown in FIG. 114 (h), the planned opening time of the hall on the next business day (for example, 12:00)
114) and the scheduled closing time (for example, 22:00) are known, so that the time is divided into time series points every 5 minutes, and the time series points are obtained every 5 minutes.
The predicted 100-division unit data shown in (g) is sequentially replaced. As a result, it is converted into the predicted time series unit data for every 5 minutes on the next business day as shown in FIG. 114 (h).
Next, in step S1196, the output data is calculated by multiplying the input data C and the predicted time series unit data. This is because by sequentially multiplying the predicted hole series amount data (input data C) by the predicted time series unit data,
As shown in FIG. 114 (i), the hall time-series forecast sales amount data (final sales amount = 1.5 million yen) is created every 5 minutes on the next business day, and the hall time-series forecast sales amount data is output. It becomes data.

L-8-9. Hall Time Series Forecast Profit Margin Data Creation Process FIG. 117 is a flowchart showing a subroutine of hole time series forecast profit margin data creation process in the hall time series performance forecast file update process. In the hall time-series forecast expected profit data creation process, first, step S12.
At 00, each data of the hole time series predicted sales amount, the number of out balls, and the number of safe balls is acquired from the hole time series performance prediction file. Next, in step S1202, each data of the same-day ball lending rate and the settlement rate is acquired from the hole day result file. This is because the profit of the hall does not simply follow the sales amount, but is affected by the number of out balls and the number of safe balls, and also depends on the ball lending rate and the settlement rate on the day. Then, step S1
The hall time series forecast expected profit data is calculated from the data acquired in 204 and stored in the hall time series performance forecast file. As a result, the time series forecast expected profit is obtained every 5 minutes, and the hall time series performance forecast file is updated. After step S1204, the process returns to the hall time-series performance prediction file update process.

M. During-Business Screen Process FIG. 118 is a flowchart showing a subroutine of the during-business screen process in the during-business process. The in-business screen process is activated when the “in-business process initialization process” in the in-business process is executed, and is stopped in the “final process in the in-business process” in the same in-business process. When the in-business screen process is activated, steps S1210 and S1
In step 212, a process of causing a predetermined screen to appear is performed, and in steps S1214 to S1220, the predetermined event process is performed (the details will be described later in subroutines). That is, in step S1210 the hall result prediction screen appearance process, in step S1212 the game stand operation screen appearance process, in step S1214 the hall result prediction screen event process, in step S1216 the game stand operation screen event process, and in step S1218 the machine type operation screen event. Processing, interrupt event screen event processing is performed in step S1220. After step S1220, the process returns to step S1214 to repeat the loop. In this way, the event process for the appearing screen is repeated, and the process is stopped when the “final process of the business process” in the business process is executed.

Next, in M-1 to M-6, the above-mentioned respective subroutines of the in-business screen process will be described in detail. M-1. Hall Result Prediction Screen Appearance Processing FIG. 119 is a flow chart showing a subroutine of the hall result prediction screen appearance processing in the in-business screen process. In the hall result prediction screen appearance process, first, step S
At 1230, the hall performance prediction screen (see FIG. 153) appears. The hall performance prediction screen is displayed in a multi-window overlay on the in-service screen. Then, step S1
At 232, the hole name and the date of the day are displayed on the hole performance prediction screen. Next, in step S1234, the opening time data on the day is acquired from the hole day result file and output to the screen. Next, in step S1236, the scheduled closing time data of the current day and the event data are acquired from the scheduled calendar file and output to the screen. As a result, the opening time,
The closing time and events of the day are displayed on the screen, making it easy to recognize the hall status. Next, in step S1238, hall result prediction screen data update processing (1) is performed (details will be described later in a subroutine). Also, in step S1240, the hall score prediction screen data update process (2) is performed (details will be described later in a subroutine). As a result, the predetermined result is corrected every second and the other predetermined contents are corrected every minute according to the actual situation, and the hall result prediction data is displayed. After step S1240, the process returns to the in-business screen process.

M-2. Hall Performance Prediction Screen Event Processing FIG. 120 is a flowchart showing a subroutine of hall performance prediction screen event processing in the in-business screen process. In the hall result prediction screen event processing, first, in step S1250, the elapsed time of the hall result prediction screen data update timer 1 is acquired. The hall result prediction screen data update timer 1 counts 1 second. Next, in step S1252, it is determined whether or not the elapsed time of the hall performance prediction screen data update timer 1 has reached 1 second. If it has not reached 1 second, step S1256 is skipped and the processing proceeds to the subsequent steps. At this time, the next and subsequent routines will wait until 1 second is reached. When 1 second is reached in step S1252, step S1254
Then, the hall performance prediction screen data updating process 1 is performed (details will be described later in a subroutine). As a result, the expected profit of the hole is updated and displayed every second.

Next, in step S1256, the elapsed time of the hall score prediction screen data update timer 2 is acquired. The hall result prediction screen data update timer 2 counts one minute. Next, in step S1258, it is determined whether or not the elapsed time of the hall result prediction screen data update timer 2 has reached 1 minute. If it has not reached 1 minute, step S1260 is skipped and the process returns to the open screen process. After all, at this time, in the routine after the next time, 1
You will have to wait for the minutes. When 1 minute is reached in step S1258, the flow advances to step S1260 to perform hall score prediction screen data update processing 2 (details will be described later in a subroutine). As a result, the expected profit of the hole is updated and displayed every minute. After step S1260, the process returns to the in-business screen process.

M-3. Hall Result Prediction Screen Data Update Process 1 FIG. 121 is a flowchart showing a subroutine of hole result prediction screen data update process 1 in the hall result prediction screen event process. In the hole result prediction screen data updating process 1, first, in step S1270, the hole day ball rental sales amount and the savings ball sales amount data are acquired from the hole day result file, and the total value thereof is displayed on the screen as the hole day sales amount. This simply sums the ball lending sales and the savings ball sales to obtain the same day sales for the hall. Next, in step S1272, the number of balls out on the day of the hole, the number of safe balls on the day, the number of safe balls, the number of bonus balls, the number of premium balls added, the amount converted, the amount stored, and the number of people visiting the store are acquired and displayed on the screen. Thereby, the data for calculating the expected profit is displayed.

Next, in step S1274, the same-day ball lending rate and the settlement rate data are acquired from the hole day result file, and the expected profit data is calculated using the sales amount, the number of out balls, and the number of safe balls. Note that the above-described arithmetic expression is used for the calculation. Next, the expected profit data calculated in step S1276 is displayed on the screen. Next, in step S1278, the hall result prediction screen data update timer 1 is initialized. As a result, the timer 1 for counting 1 second is initialized to [0], and counting for 1 second is started again. Therefore, the expected profit of the hole is updated and displayed every second. Step S1
After 278, the process returns to the hall result prediction screen event processing.

M-4. Hall Result Prediction Screen Data Update Process 2 FIG. 122 is a flowchart showing a subroutine of hole result prediction screen data update process 2 in the hall result prediction screen event process. In the hole result prediction screen data update processing 2, first, in step S1280, the hole day / time series sales amount and the expected profit data are acquired from the hole day / time series result file and displayed on the graph of the screen (hole performance prediction screen) with a solid line. (See FIG. 153). Next, in step S1282, the hall time series forecast sales amount and the expected profit data are acquired from the hall time series performance forecast file,
The difference between the sales amount and the profit as of the day is calculated.
This is to obtain the data for calculating the difference between the actual measurement value up to the present time and the predicted value, and correcting the graph showing the transition of sales and profit until the closing of the store. Next, in step S1284, differences are added to all the time-series predicted sales amount and expected profit data after the current time, and the results are output as dotted lines on the screen graph. As a result, in the hall performance prediction screen, the graph showing the transition of sales and profits until the closing of the store is corrected in consideration of the difference between the actual measurement value up to the present and the prediction value, and is displayed with a dotted line.

[0295] Next, in step S1286, the hole predicted sales amount data is acquired from the hole performance prediction file, and the result of adding the calculated difference to the value is output to the screen as the predicted value when the store is closed. As a result, the predicted sales amount when the store is closed is corrected in consideration of the difference between the actual measurement value of the sales amount up to the present time and the predicted value, and the corrected sales amount is displayed on the hall performance prediction screen. Next, in step S1288, the hole time-series performance prediction file is used to obtain the hole time-series predicted out ball number, safe ball number, bonus ball number, premium additional ball number, redemption amount, and accumulated ball amount data, and the difference from the data as of the day Are calculated respectively. This is to obtain the data for calculating the difference between the actual measurement value up to the present time and the predicted value, and correcting each predicted data (displayed in the display format instead of the graph display) until the store is closed. Is.

Next, in step S1290, the number of holes predicted out, the number of safe balls,
Number of bonus balls, number of premium additional balls, number of people visiting the store, redemption amount,
The accumulated amount data is acquired, and the result of adding the calculated differences to these values is output to the screen as a predicted value when the store is closed. As a result, the predicted data at the time of closing (that is, the predicted number of out balls, the number of safe balls, the number of bonus balls, the number of premium additional balls) is taken into consideration in consideration of the difference between the actual measured values of the above data up to the present and their predicted values. , Data on the number of people visiting the store, redemption amount, and accumulated amount)
Is corrected and displayed in a tabular form on the hole performance prediction screen (see FIG. 153). Next, in step S1292, the ball lending rate, the settlement rate data, and the sales amount of the predicted value at the time of closing,
Predicted profit data when the store is closed is calculated using the number of out balls and the number of safe balls, and is output to the screen. Next, in step S1294, the hall result prediction screen data update timer 2
Is initialized. As a result, the timer 2 for counting 1 minute is initialized to [0], and the counting of 1 minute is started again. Therefore, the expected profit of the hole is updated and displayed every minute. Step S1294
After that, the process returns to the hall result prediction screen event processing.

M-5. Gaming Machine Operation Screen Appearance Processing FIG. 123 is a flowchart showing a subroutine of the gaming machine operation screen appearance processing in the in-business screen process.
In the game stand operation screen appearance process, first, step S1300.
The game console operating screen appears in the foreground, and multiple machine-specific operating screens and interrupt event screens appear in the foreground.
This is one of the screens open in the multi window
This is to bring the game console operating screen to the front so that it is easier to see. Next, in step S1302, all model names installed in the hall are displayed on the buttons in the menu area (see FIG. 154 (b)). Then, step S13
In 04, model-specific operation screen data update processing is performed (details will be described later in a subroutine). As shown in FIG. 155, the operation status is displayed on the screen for each model, and, for example, the row of the machine numbers during the big hit is blinked. Next, in step S1306, the interrupt event monitoring timer is initialized. The interrupt event monitoring timer monitors whether or not an interrupt occurs when displaying an error or calling a salesclerk on the screen, and monitors every 0.3 seconds. Step S
After 1306, the process returns to the in-business screen process.

M-6. Game Table Operation Screen Event Processing FIG. 124 is a flowchart showing a subroutine of game machine operation screen event processing in the in-business screen process. In the game table operation screen event process, first, step S
At 1310, as shown in FIG. 157 (b), the game console operating screen is displayed in the foreground, and all machine names, calling, and error icons are displayed on the buttons in the menu area on the game console operating screen. , It is determined whether or not the icon button is pressed. This is to determine whether either the call icon or the error icon has been pressed.
When the icon button is pressed, step S1312
The data of the interrupt event monitoring area corresponding to the position number assigned to the icon button pressed by is moved to the representative position of the area. This is to bring to the latest position (position number = “0” position) when the call or error icon button is pressed. Next, in step S1314, the data in the interrupt event monitoring area vacated by the movement is filled by shifting the data. As a result, the data behind the interrupt event monitoring area is shifted to the interrupt event monitoring area vacated by the movement. After step S1314, the process jumps to step S1320.

On the other hand, if the icon button is not pressed in step S1310, the flow advances to step S1316 to determine whether the "model name button" has been pressed. this is,
As shown in FIG. 157 (b), when the game console operation screen is displayed in the foreground and all model names are displayed on the buttons in the menu area on the game console operation screen, one of the "machine name button" It is to judge whether or not the operation of selecting any of the model names by pressing "" has been performed. If the "model name button" is pressed, the process advances to step S1318 to perform a model-specific operation screen appearance process (details will be described later in a subroutine), and then the process advances to step S1320. As a result, the model-specific operation screen (see FIG. 155) appears in the multi-window. If the "model name button" is not pressed, the process jumps to step S1318 and proceeds to step S1320.

In step S1320, the elapsed time of the interrupt event monitoring timer is acquired. Then, step S13
In step 22, it is determined whether or not the elapsed time of the timer reaches 0.3 seconds, and when it reaches 0.3 seconds, the process proceeds to step S1324 to perform the interrupt event monitoring timer processing (details will be described later in a subroutine). . This is to monitor whether or not an interrupt for displaying an error or calling a clerk is made on the screen every 0.3 seconds and perform necessary processing. After step S1324, the process advances to step S1326. If 0.3 seconds has not been reached in step S1322, step S1324 is skipped and step S1 is performed.
Proceed to 326. In step S1326, the elapsed time of the model-specific operating screen data update timer is acquired. Next, in step S1328, it is determined whether or not the elapsed time of the timer has reached 1 second, and when 1 second is reached, the process proceeds to step S1330 to perform model-specific operating screen data update processing (details will be described later in a subroutine). , Return to the on-screen screen process. This is to update the data of the operation screen for each model every one second. If the elapsed time of the model-specific operating screen data update timer has not reached 1 second, the routine of this time is ended and the process returns to the in-business screen process.

M-6-1. Model-Specific Operation Screen Data Update Process FIG. 125 is a flowchart showing a subroutine of the model-specific operation screen data update process in the game console operation screen appearance process and the like. In the model-specific operation screen data update process, first, in step S1340, the P machine same day result file is used.
Create grade files for all models on the day. Then
In step S1342, the contents of the grade-specific result file are displayed on the corresponding model-specific operation screens. As a result, the contents of the results by vehicle on the day are displayed in real time on the operating screen for each model, but if not all can be displayed on the screen, they are scrolled and displayed on the screen by operating the scroll bar.

Next, in step S1344, the game status data in the P machine day result file is checked, and the in-game machine number and the out-of-game machine number are displayed in different colors. This is shown in FIG.
As shown in, for example, the colors of the “105” series and the “106” series are changed (displayed in red) to indicate that the game is in progress, and the out-of-game machine numbers remain white. Next, in step S1346, the prize status data of the P machine day result file is checked, and the column of the machine numbers in the prize is blinked. This is, for example, "10" as shown in FIG.
When the "2" series is in the special prize, the column is blinked to let the player recognize at a glance that it is a big hit. Then
In step S1348, the model-specific operation screen update timer that counts the time for updating the data of the model-specific operation screen every one second is initialized, and the process returns to the gaming machine operation screen appearance process.

M-6-2. Model-Specific Operation Screen Appearance Processing FIG. 126 is a flowchart showing a subroutine of model-specific operation screen appearance processing in the gaming table operation screen event processing. In the operation screen appearance process for each model, first, step S
In response to pressing of the “model name” button in 1350, a model-specific operation screen of the target model appears (it appears by pop-up). Then, in step S1352, the "model name" button of the target model is deleted from the game machine operating screen. This is because the sub-screen (model-specific operating screen) was made to appear on top of the main screen. It is something to keep. As a result, it is possible to eliminate the problem that the operation screens for each model appear in a plurality of layers and the arithmetic processing is delayed. After step S1352, the process returns to the game machine operation screen event process.

M-6-3. 127. Interrupt Event Monitoring Timer Processing FIGS. 127 and 128 are flowcharts showing a subroutine of the interrupt event monitoring timer processing in the gaming machine operation screen event processing. In the interrupt event monitoring timer process, first in step S1360, the representative position of the interrupt event monitoring area is checked. Next, in step S1362, it is determined whether or not there is data at the representative position, that is, whether or not there is data at the latest position (position of position number = "0"). If there is data, an interrupt event screen is displayed in step S1364. (See FIG. 157) is determined. Immediately after the call or error packet is transmitted from the gaming machine and the data is input to the representative position, the interrupt event screen has not appeared, so that the interrupt event screen appears in step S1366. . As a result, the interrupt event screen as shown in FIG. 157 is displayed in the foreground as a multi-window.

Next, in step S1368, the machine number data of the representative position of the interrupt event monitoring area is displayed on the screen. For example, in the example shown in FIG. 158 (a), "103"
It is displayed as a series. Next, in step S1370, it is determined whether or not the interrupt event at the representative position is “call”. If the interrupt event is "call", step S1
At 372, the message "call" is output to the screen. As a result, as shown in FIG. 158 (a), for example, a message "You are calling" is displayed on the interrupt event screen, and the message is transmitted to the manager who is watching the screen.

If the interrupt event is not "call" in step S1370, it is determined that the packet is an error packet,
In step S1374, the error code and error coping method are output to the screen by referring to the detailed code of the representative position and the P machine detailed error registration file. As a result, detailed information on the error name and the error coping method is read from the P machine detailed error registration file storing the information on the interrupt event monitoring area as shown in FIG. 69, and for example, FIG. 158 (b). As shown in, the message "Please open the ball jamming error occurrence panel and remove the ball" is displayed on the interrupt event screen and informs the manager who is watching the screen.

On the other hand, if the interrupt event screen has already appeared in step S1364, the process jumps to step S1376. If there is no data at the representative position in step S1362, it is determined that the calling or error packet from the gaming machine is not transmitted, and step S137.
It branches to 8 and determines whether or not the interrupt event screen appears. If the interrupt event screen appears, the interrupt event screen is deleted in step S1380, and the step S1380 is executed.
Proceed to 1376. This is because there is no data at the representative position, and if the interrupt event screen appears, the interrupt event screen is deleted. Also, in the case of an error release packet, the interrupt event screen will be deleted. If the interrupt event screen does not appear in step S1378, the process jumps to step S1380 and proceeds to step S1376.

In step S1376, all icon buttons are deleted. This is to see if all icon buttons are erased and the icon buttons are displayed once.
This is because it is decided after monitoring the data in the interrupt event monitoring area. When all icon buttons are deleted in step S1376, the process advances to step S1382 to specify a position number other than the representative position of the interrupt event monitoring area. That is, a position number subsequent to the rear other than the position number = "0" such as the position number = "1" is designated. Next, in step S1384, an icon button is made to appear at a position on the screen corresponding to the designated position number. For example, if the position number is “1”, the icon button appears at the leftmost position on the lower side of the screen as shown in FIG. 157 (b).

Next, in step S1386, the unit number data and event code data of the designated position number are displayed on the icon button. For example, position number =
If "1", as shown in FIG. 157 (b), the unit number = on the icon button displayed on the leftmost side on the lower side of the screen.
“103”, event code = “call” are displayed. Next, in step S1388, a designated position number is assigned to the icon button. For example, if the position number = "1" is designated this time, the position number = "1" is assigned to the icon button. Next, in step S1390, the next position number is designated. For example, if the position number = "1" is designated this time, the position number = "2" is designated next.

Next, in step S1392, it is determined whether or not the next position number exists, and if it exists, the process returns to step S1384 and the same loop is repeated. In the next loop, the same processing is performed for the position number = “2”. At this time, since the position number = “2”, the icon button is made to appear at the second position from the left side on the lower side of the screen this time, as shown in FIG. 157 (b). In this way, the next position number is sequentially specified, and when the next position number does not exist in step S1392, the process is skipped to step S1394 and an error display or a clerk call display is made. Including 0.3
Initialize the interrupt event monitoring timer monitored every second, and return to the game console operation screen event processing.

M-7. Model-Specific Operation Screen Event Processing FIG. 129 is a flowchart showing a subroutine of model-specific operation screen event processing in the in-business screen process. In the operation screen event processing for each model, first, step S
In 1400, it is determined whether or not there is a model-specific operation screen that has appeared, and if there is no model-specific operation screen that has appeared, this routine is terminated and returns to the in-business screen process. If there is a model-specific operation screen that has appeared, the process advances to step S1402 to determine whether the "close" button has been pressed. This is to determine whether or not the “close” button displayed at the upper right of the model-specific operation screen as shown in FIG. 156 has been operated. If the "close" button is pressed, the process branches to step S1404 to pop down the model-specific operating screen for which the "close" button is pressed. This closes the corresponding model-specific operation screen.

Next, in step S1406, the button of the target model appears on the game machine operating screen. This is because, since the model-specific operating screen has been closed, the operation button of the target model is displayed again so that the model-specific operating screen can be displayed. That is, the procedure returns to the previous operation procedure. After step S1406, the process returns to the in-business screen process. If NO in step S1402 (when the “close” button is not pressed), the process advances to step S1408 to determine whether the scroll bar has been operated. If you are not operating the scroll bar,
Return to the in-business screen process. If the scroll bar is operated, the process branches to step S1410 to scroll the screen display. As a result, the next model number on the appearing model-specific operation screen is sequentially scrolled. After step S1410, the process returns to the in-business screen process.

M-8. Interrupt Event Screen Event Processing FIG. 130 is a flowchart showing a subroutine of interrupt event screen event processing in the in-business screen process. In the interrupt event screen event process, first in step S1420, it is determined whether or not the interrupt event screen has appeared. If not, the routine of this time is ended and the process returns to the open screen process. When the interrupt event screen appears, it is determined in step S1422 whether the "icon" button has been pressed. If not, the process similarly returns to the in-business screen process. If the "icon" button is pressed, the flow advances to step S1424 to shift the data other than the representative position of the interrupt event monitoring area backward.

This is because the data of position number = “1”, position number = “2”, ...
"3", ... and so on. As a result, the position number = “1” is vacant. Next, in step S1426, the data at the representative position is moved to the position of position number = "1". As a result, the data at the latest position (position number = "0") moves to the position number = "1". Next, in step S1428, the data of the representative position is cleared and the process returns to the in-business screen process. In this way, when the "icon" button is pressed while the interrupt event screen as shown in FIG. 157 (a) appears, the data at the representative position moves to the position of position number = "1". , The interrupt event screen disappears and is displayed as an icon.

N. Closing Screen Process FIG. 131 is a flowchart showing a subroutine of the closing screen process. The closing screen process is activated by the closing confirmation process and ends when the management analyzer 12 goes offline. When the closing screen process is activated, step S15
In steps 00 to S1508, predetermined processing relating to the closed screen is performed (the details will be described later in subroutines). That is, the closing screen process initialization process is performed in step S1500, the weather input process is performed in step S1502, the aggregation process 1 standby process is performed in step S1504, and the step S1 is performed.
Post-closing business data editing processing at 506, step S150
At 8, the totaling process 2 standby process is performed. Then, step S1
After 508, when the management analyzer 12 goes offline, the closing screen process ends.

Next, in each of N-1 to N-5, each of the above subroutines of the closing screen process will be described in detail. N-1. Store Closed Screen Process Initialization Processing FIG. 132 is a flowchart showing a subroutine of store closed screen process initialization processing in the store closed screen process. In the closing screen process initialization process, step S15
At 10, the weather input screen appears. This is to open a screen for inputting today's weather when the store is closed as shown in FIG. 159, and to improve the accuracy of data prediction based on the weather. It is also possible to choose to ignore the weather. Next, in step S1512, the weather consideration flag is reset. This clears the previous weather consideration flag. After step S1512, the process returns to the closing screen process.

N-2. Weather Input Processing FIG. 133 is a flowchart showing a subroutine of weather input processing in the closing screen process. In the weather input processing, it is determined in step S1520 whether the weather button of the day has been pressed, and if pressed, the color of the pressed button is changed in step S1522. This corresponds to the case where any of the weather buttons is pressed when the weather input screen capable of inputting today's weather is open when the store is closed as shown in FIG. 159. After step S1522, the process returns to step S1520 again. Therefore, when the weather button is pressed, the color of the weather button is simply changed. When the color of the weather button is changed and the process returns to step S1520, the determination result is NO and step S152
Proceed to 4. On the other hand, if none of the weather buttons is pressed when the first routine is started, step S
Proceed to 1524.

[0318] In step S1524, it is determined whether or not the weather button for the next business day has been pressed. If the weather button for the next business day has been pressed, the color of the button pressed in step S1526 is changed. This corresponds to the case where any one of the weather buttons of the next business day is pressed when the weather input screen in which the weather of the next business day can be input at the time of closing the shop is opened as shown in FIG. 159. Next, in step S1528, the weather consideration flag is set, and the process returns to step S1520. The weather consideration flag is set to consider the weather of the next business day in the predicted weather data of the next business day. If the weather button for the next business day is not pressed in step S1524, the flow advances to step S1530 to determine whether the "ignore weather" button has been pressed. When the "Ignore weather" button is pressed, the color of the pressed button is changed in step S1532. Next, in step S1534, the weather consideration flag is reset and the process returns to step S1520. As a result, the forecast data for the next business day does not consider the weather of the next business day.

If the "ignore weather" button is not pressed in step S1530, the flow advances to step S1536,
It is determined whether or not the "confirm" button has been pressed. If the "confirm" button is not pressed, the process returns to step S1520 to repeat the same loop, and if the "confirm" button is pressed, the process proceeds to step S1538. By pressing the "confirm" button,
The operation of the button whose color has been changed is confirmed. In step S1538, it is determined whether the weather button for the day has not been pressed even once. If the weather button of the day has not been pressed once, the process returns to step S1520 and the same loop is repeated. If the weather button of the day is pressed even once, the process exits to step S1540.

In step S1540, the weather data of the day selected in this screen is set in the weather data of the hole day result file. Next, in step S1542, it is determined whether or not the weather consideration flag is set, and when the weather consideration flag is set, in step S1544, the next weather selected in this screen is added to the forecast weather data of the hole performance forecast file. Set day weather, step S15
Proceed to 46. As a result, in the hall performance prediction file that predicts the data of the next business day, the data is predicted in consideration of the parameter of weather. On the other hand, if the weather consideration flag is not set (reset) in step S1542, step S1544.
And jump to step S1546. Step S
At 1546, the hall operating status data of the hall day result file is set to "total 1". As a result, the status indicating the operating state of the hall is in the process of “total 1”. Then, in step S1548, the weather input screen is popped down. This closes the weather input screen. After step S1548, the process returns to the closing screen process.

N-3. Aggregation processing 1 standby processing FIG. 134 is a flowchart showing a subroutine of aggregation processing 1 standby processing in the closing screen process. In the tallying process 1 standby process, a tallying screen appears in step S1550. Although the counting screen is not shown, for example, a message “I am counting now!” Is displayed on the screen. Next, in step S1552, the aggregation monitoring timer is initialized. The aggregation monitoring timer counts the time for securing data every one second. Next, in step S1554, the elapsed time of the aggregation monitoring timer is acquired, and in step S1556, it is determined whether or not the elapsed time of the aggregation monitoring timer has reached 1 second. If 1 second is not reached, the process returns to step S1554 and repeats the process. If 1 second is reached, the process goes to step S1558 to obtain hole operating state data from the hole day result file. Next, it is determined whether or not the hall operating state data acquired in step S1560 is “business after closing”. If NO, the process returns to step S1552 to repeat the loop. Then, when the hall operating state data becomes “business after closing”, the process goes to step S1562 to erase the totalization display screen. After step S1562, the process returns to the closing screen process.

N-4. Business Data Editing Process After Closing FIG. 135 is a flowchart showing a subroutine of business data editing process after closing in the store screen process.
In the post-closing business data editing process, the next business setting screen appearance process is performed in step S1570 (details will be described later in a subroutine). This is the next sales setting screen (see Fig. 160)
Is to appear. Then, step S1572.
Then, it is determined whether or not the platform adjustment confirmation screen appears, and if not, the process branches to step S1574 to perform the next business setting process (details will be described later in a subroutine). This is to perform the processing necessary for the next business setting.

Next, in step S1576, it is determined whether or not the "end & platform adjustment" button has been pressed. If the "end & platform adjustment" button has been pressed, the flow advances to step S1576 to see if the menu number is "0". Determine whether or not. The menu number = “0” corresponds to the number for instructing the menu for causing the platform adjustment confirmation screen as shown in FIG. 161 to appear.
If the menu number is "0", the process advances to step S1580 to display the platform adjustment confirmation screen. As a result, FIG.
As shown at 61, a platform adjustment confirmation screen for selecting an item for platform adjustment is popped up. Then, step S1582.
Acquire the selected platform adjustment item from the platform adjustment item file with and display it on the screen. In this case, as shown in FIG. 161, the selected platform adjustment item is displayed with the transfer area marked. After step S1582, the process returns to step S1572. On the other hand, if the "end & stand adjustment" button is not pressed in step S1576, or if the menu number is not "0" in step S1578, the process returns to step SS1572.

If the platform adjustment confirmation screen has already appeared in step S1572, the flow advances to step S1584 to determine whether the "stop" button has been pressed. Erase the adjustment confirmation screen. This is because the "Cancel" button was pressed on the platform adjustment confirmation screen, so that the screen was deleted. If the "Cancel" button is not pressed, the flow advances to step S1588 to determine whether the transfer item has been clicked. The item of transfer is an item selected as the machine adjustment, and when selected, the machine adjustment data is transferred to the gaming machine. When the transfer item is clicked in step S1588, the attention (mark) of the clicked part is set in step S1590, and the attention is released, and if the attention is released, the attention is set. This is because each time the transfer item is clicked, the setting or cancellation operation is performed. In this way, the platform adjustment items can be freely set / released. After step S1590, the process returns to step S1572.

On the other hand, if it is determined in step S1588 that the transfer item is not clicked, the flow advances to step S1592 to determine whether the "execute" button has been pressed. "Run"
When the button is not pressed, the process returns to step S1572,
When the "execute" button is pressed, the flow advances to step S1594 to count the "transfer" locations where the attention (mark) is set. Next, it is determined whether or not the number of points counted in step S1596 is five, and if not five, step S
Returning to 1572, the process is redone, and if there are five locations, the process advances to step S1598 to store the platform adjustment item for which the attention (mark) is set in the platform adjustment item file.

Next, in step S1600, data is acquired from the next business setting file and stored in the hall performance prediction file. This will predict the hall performance on the next business day. Next, in step S1602, data is acquired from the next business setting file, the next business day is set in the predicted date data, and the data is stored in the P machine performance prediction file. As a result, the P machine performance of the next business day is predicted. Then
In step S1604, the hall operating status data of the hall day result file is set to "stand adjustment". Next, in step S1606, the stand adjustment confirmation screen and the next business setting screen are deleted. After step S1606, the process returns to the closing screen process. In this way, open the platform adjustment confirmation screen on the next business setting screen in a multi-window, perform processing such as setting platform adjustment items and store it in the platform adjustment item file, or use the forecast data of the next business day for hall results. Processing such as storing in a prediction file or a P machine result prediction file is performed.

N-4-1. Next Business Setting Screen Appearance Processing FIG. 136 is a flowchart showing a subroutine of next business setting screen appearance processing in the post-closing business data editing processing. In the next sales setting screen appearance process, step S1
At 610, the next sales setting screen appears. Next, in step S1612, next business setting screen restoration processing is performed (details will be described later in a subroutine). After step S1612, the process returns to the business data editing process after closing the store.

N-4-1a. Next Business Setting Screen Restoration Processing FIG. 137 is a flowchart showing a subroutine of the next business setting screen restoration processing in the next business setting screen appearance processing. In the next business setting screen restoration process, step S1
At 620, the P machine predicted out ball number data whose predicted date data is the next business day and the planned game setting value data whose predicted date data is the current day are acquired from the P machine result prediction file and stored in the next business setting file. . Then, step S1
At 622, the next sales setting screen data output process is performed (details will be described later in a subroutine). This is to recalculate and display the predicted data of the next business day (displayed on the next business setting screen shown in FIG. 160) when the planned game setting value is changed or newly set.

Next, in step S1624, the predicted visitor number data is acquired from the hall result prediction file and displayed on the screen. As a result, the predicted number of people visiting the store (for example, 2102) is displayed on the next sales setting screen shown in FIG. Next, in step S1626, the opening and closing time data of the next business day is acquired from the scheduled calendar file,
Calculate the business hours for the next business day. Then, step S
At 1628, the hole predicted out ball number data is acquired from the hole performance prediction file, the predicted operating rate of the next business day is calculated, and the calculated result is displayed on the screen. In this case, the number of installed gaming machines is acquired from the model information file. In addition, the operating rate of the hole is calculated from the above-described calculation formula based on the concept of the number of predicted balls out of the hole × 0.6 (second / one shot). As a result, the predicted operating rate (for example, 76.2%) is displayed on the next sales setting screen shown in FIG. Next, in step S1630, the cursor is superimposed and displayed on the display of the setting value of the P machine displayed at the beginning of the “unit-specific setting” area. As a result, the cursor first waits and is displayed at the head position of the "setting by vehicle" area of the next sales setting screen shown in FIG. After step S1630, the process returns to the next business setting screen appearance process.

N-4-1a-1. Next Business Setting Screen Data Output Process FIG. 138 is a flowchart showing a subroutine of the next business setting screen data output process in the next business setting screen restoring process. In the next sales setting screen data output process,
In step S1640, the P machine whose scheduled game setting value in the next business setting file is changed or newly set from the previous time is targeted. This is because the data of the P machine whose scheduled game setting value has been changed or newly set is recalculated and displayed. Next, in step S1642, each prediction data of the target P machine is acquired from the model game setting value file. Next, in step S1644, predicted sales amount and expected profit data of the target P machine are calculated. Then, step S1646.
Then, the predicted sales amount data of all P machines are summed up to calculate the hole predicted sales amount data and stored in the next business setting file.

Next, in step S1648, the contents of the predicted hole sales data are stored in the targeted hole sales data. Next, in step S1650, the predicted expected profit data of all P machines are summed to calculate the hole predicted expected profit data, which is stored in the next business setting file. Next, in step S1652, the content of the expected hole profit data is stored in the expected hole profit data. Next, in step S1654, the contents of the hole target sales amount data and the hole target expected profit data are displayed on the screen. Next, in step S1656, scheduled game set value data of all P machines and P machine predicted out ball number data are acquired from the next business setting file and displayed on the screen. Then, step S165
In step 8, the menu number is set to "0" and the process returns to the next business setting screen restoration process. In this way, when the planned game setting value is changed or newly set, the forecast data of the next business day is recalculated and displayed on the next business setting screen.

N-4-2. Next Business Setting Process FIG. 139 is a flowchart showing a subroutine of the next business setting process in the post-closing business data editing process.
In the next business setting process, it is determined whether or not the sales amount data change button is pressed in step S1660. this is,
It is to judge whether or not the user has operated by clicking the data change button (two buttons for increasing the sales amount and a button for decreasing the sales amount) in the line of the sales amount on the next sales setting screen displayed in FIG. 160. . If the sales amount data change button is pressed, the process proceeds to step S1662 to perform target sales amount change processing (details will be described later in a subroutine), and then returns to the post-closing business data editing processing. As a result, the hall target sales amount data is adjusted according to the operation of the sales amount data change button, recalculated, and displayed on the screen. On the other hand, if the sales amount data change button is not pressed, the flow advances to step S1664 to determine whether the profit data change button is pressed. This is shown in FIG.
It is to judge whether or not the user has operated by clicking the data change button (two buttons for increasing profit and decreasing profit) in the profit line on the next sales setting screen displayed in 60.

If the profit data change button is pressed, the flow advances to step S1666 to perform target profit change processing (details will be described later in a subroutine), and thereafter returns to the post-closing business data editing processing. Thereby, the hole target profit data is adjusted according to the operation of the profit data change button, recalculated and displayed on the screen. On the other hand, if the profit data change button is not pressed, the flow advances to step S1668 to determine whether or not the “unit-specific setting change” button has been pressed. The "change setting for each unit" button is used to perform an operation for changing and recalculating and displaying the prediction data for each unit.
When the "Change settings by unit" button is pressed, step S16
Proceeding to 70, the setting value change process for each vehicle is performed (details will be described later in a subroutine), and then the process returns to the post-closing business data editing process. As a result, the prediction data is changed for each table, recalculated, and displayed on the screen.

[0334] If the "Change settings for each unit" button is not pressed, the flow advances to step S1672 to determine whether the scroll bar has been operated. The scroll bar here is used to perform an operation of scrolling each of the stands displayed in the area for each stand. When the scroll bar is operated, the process advances to step S1674 to scroll the display area, and returns to the business data editing process after closing the store. As a result, the display area of the setting for each unit is scrolled. If the scroll bar is not operated, the flow advances to step S1676 to determine whether or not the setting value area has been clicked. The setting value area shows the game setting value of each machine, and the color changes when selected. 10 on the default screen of the next sales setting screen
The cursor is on the 1st line. When the area of the set value is clicked, the flow advances to step S1678 to place the cursor on the clicked area. If the user does not click the setting value area, the process advances to step S1680 to determine whether the "increase setting" button has been pressed. The "increase setting" button is used to increase (increase) the game setting value of the P machine.

If the "increase setting" button is pressed, the flow advances to step S1682 to perform setting UP processing (details will be described later in a subroutine), and then returns to the post-closing business data editing processing. As a result, the game setting value of the selected platform becomes high. If the "increase setting" button has not been pressed, the flow advances to step S1684 to determine whether the "decrease setting" button has been pressed. The “decrease setting” button is used to decrease (decrease) the game setting value of the P machine. If the "decrease setting" button is pressed, the flow advances to step S1686 to perform setting DOWN processing (details will be described later in a subroutine), and then returns to the post-closing business data editing processing. As a result, the game setting value of the selected machine is lowered. If the "decrease setting" button is not pressed, the flow advances to step S1688 to determine whether or not the "hall score calculation" button has been pressed.

The "hall score calculation" button is used to perform an operation for requesting calculation of hall score data. If the "Hall score calculation" button is pressed, the process advances to step S1690 to perform a hall score calculation process (details will be described later in a subroutine), and then returns to the post-closing business data editing process. As a result, the hall score is calculated and displayed on the screen. If you do not press the "calculate hall results" button,
In step S1692, it is determined whether the "undo" button has been pressed. The "Restore" button is used to return to the initial display state of the next business setting screen. If the "Restore" button is pressed, step S1694
Then, the next business setting screen restoration process is performed (details will be described later in a subroutine), and then the process returns to the post-closing business data editing process. As a result, even if various button operations have been performed until now, the initial display state of the next sales setting screen (the state in which data is not changed by button operation)
Is returned to. If the "Restore" button is not pressed, the process returns to the business data editing process after closing the store.

N-4-2a. Target Sales Amount Change Process FIG. 140 is a flowchart showing a subroutine of the target sales amount change process in the next business setting process. In the target sales amount change processing, it is determined in step S1700 whether the menu number is "0" or "1". The menu number “0” or “1” corresponds to a state where the profit data is not calculated. Profit data is calculated by menu number =
"2". If the menu number is not "0" or "1" (otherwise), the process returns to the next business setting process. If the menu number is "0" or "1", the process advances to step S1702 to set the menu number to "1". This enables calculation of sales amount data. Next, in step S1704, the hole target sales amount data of the next business setting file is adjusted and displayed on the screen. As a result, the hall target sales amount data is adjusted according to the operation of the sales amount data change button, recalculated, and displayed on the screen. Step S1704
After, the process returns to the next business setting process.

N-4-2b. Target Profit Change Process FIG. 141 is a flowchart showing a subroutine of the target profit change process in the next business setting process. In the target profit change process, it is determined in step S1710 whether the menu number is "0" or "2". The menu number “0” or “2” corresponds to a state where the sales amount data is not calculated. Menu number =
It is "1". If the menu number is not "0" or "2" (otherwise), the process returns to the next business setting process. If the menu number is "0" or "2", the flow advances to step S1712 to set the menu number to "2". This allows the calculation of profit data. Next, in step S1714, the hole target expected profit data in the next business setting file is adjusted and displayed on the screen. As a result, the hole target expected profit data is adjusted according to the operation of the profit data change button, recalculated and displayed on the screen. Step S17
After 14, the process returns to the next business setting process.

N-4-2c. Individual-Unit Setting Change Processing FIG. 142 is a flowchart showing a subroutine of individual-vehicle setting changing processing in the next business setting processing. In the setting change process for each machine, it is determined in step S1720 whether the menu number is "1". Menu number is "1"
Is equivalent to calculation of sales amount data. Menu number =
When it is "1", the process proceeds to step S1722, and it is determined whether the target sales amount> the predicted sales amount, that is, the target sales amount is larger than the predicted sales amount. If the target sales amount is larger than the predicted sales amount, the process advances to step S1724 to perform the setting change updating process for each vehicle 1 (details will be described later in a subroutine). As a result, the data is recalculated so as to simulate the case where the target sales amount is larger than the predicted sales amount, and the result is displayed on the screen. After step S1724, the process returns to the next business setting process. On the other hand, if the target sales amount is smaller than the predicted sales amount, the flow advances to step S1726 to perform the setting change updating process 2 for each vehicle (details will be described later in a subroutine). As a result, the data is recalculated so as to simulate the case where the target sales amount is smaller than the predicted sales amount, and the result is displayed on the screen. After step S1726, the process returns to the next business setting process.

[0340] In step S1720, the menu number =
If it is not "1", the flow advances to step S1728 to determine whether the menu number is "2". The menu number “2” corresponds to the calculation of expected profit data. When the menu number is “2”, the process proceeds to step S1730 and it is determined whether target profit> predicted profit, that is, the target profit is larger than the predicted profit. If the target profit is larger than the predicted profit, the flow advances to step S1732 to perform the setting change update process 3 for each vehicle (details will be described later in a subroutine). As a result, the data is recalculated so as to simulate the case where the target profit is made larger than the predicted profit, and the result is displayed on the screen. Step S1
After 732, the process returns to the next business setting process. On the other hand, if the target profit is smaller than the predicted profit, step S17.
Proceeding to step 34, the setting change updating process 4 for each machine is performed (details will be described later in a subroutine). As a result, the data is recalculated so as to simulate the case where the target profit is made smaller than the predicted profit, and the result is displayed on the screen. After step S1734, the process returns to the next business setting process.

N-4-2c-1. Individual Setting Update Processing 1 FIG. 143 is a flowchart showing a subroutine of individual setting update processing 1 in the individual setting change processing. In the per-vehicle setting update processing 1, in step S1740, the next business setting file is searched for the P machine having the largest predicted out ball number data. Select only one. Then
The scheduled game setting value data of the P machine selected in step S1744 is updated by "-1". For example, when the game setting value is "2", the game setting value is reduced to "1". Reducing the game setting value corresponds to an increase in sales amount for the hall (which means that it is difficult for the customer to generate a big hit).

Next, in step S1746, the predicted data corresponding to the updated setting values is acquired from the model game setting value file, and the predicted sales amount data of the P machine is calculated. This is a simulation of how much the predicted sales amount data of the P machine is increased by decreasing the game setting value. Next, in step S1748, the predicted sales amount data of all P machines are summed up to calculate the predicted sales amount data of the hall. Next, in step S1750, the difference between the target sales amount and the predicted sales amount is calculated, and step S17
It is determined whether or not the difference calculated in 52 is minimum (is within an allowable range). That is, it is determined whether or not what is aimed for as the target sales amount is simulated as the predicted sales amount.

If the difference between the target sales amount and the predicted sales amount is not the minimum in step S1752, the operation proceeds to step S1754, and the P machine having the next largest predicted out ball number value (the P machine with a large number of operations) is selected. Returning to S1742, the same loop is repeated. Then, by repeating the loop, when the difference between the target sales amount and the predicted sales amount becomes minimum,
The operation proceeds to step S1756, the next business setting screen data output process is performed, and the process returns to the per-vehicle setting change process. By performing the above processing, the data for simulating the case where the target sales amount is larger than the predicted sales amount up to now is recalculated, and the result is displayed on the screen.

N-4-2c-2. Individual Setting Update Processing 2 FIG. 144 is a flowchart showing a subroutine of individual setting update processing 2 in the individual setting change processing. In the per-vehicle setting update processing 2, in step S1760, the next business setting file is searched for the P machine having the smallest predicted out ball number data. In step S1762, when there are a plurality of corresponding P machines, a random number is used to determine 1 Select only one. Then
The planned game setting value data of the P machine selected in step S1764 is updated by "+1". For example, when the game setting value is "2", the game setting value is increased to "3". Increasing the game setting value corresponds to a decrease in sales amount for the hall (which means that the jackpot is likely to occur for the customer).

Next, in step S1766, the prediction data corresponding to the updated setting value is acquired from the model game setting value file, and the predicted sales amount data of the P machine is calculated. This simulates how much the predicted sales amount data of the P machine becomes smaller by increasing the game setting value. Next, in step S1768, the predicted sales amount data of all P machines are totaled to calculate the predicted sales amount data of the hall. Next, in step S1770, the difference between the target sales amount and the predicted sales amount is calculated, and step S17
It is determined whether or not the difference calculated in 72 is the minimum (is within the allowable range). That is, it is determined whether or not what is aimed for as the target sales amount is simulated as the predicted sales amount. If the difference between the target sales amount and the predicted sales amount is not the minimum in step S1772, the process proceeds to step S1774, and the value of the predicted out ball number is next smaller P
The machine is selected, the process returns to step S1762 and the same loop is repeated. When the difference between the target sales amount and the predicted sales amount is minimized by repeating the loop, the process proceeds to step S1776, the next business setting screen data output process is performed, and the process returns to the individual unit setting change process. By performing the above processing, data for simulating the case where the target sales amount is made smaller than the predicted sales amount up to now is recalculated, and the result is displayed on the screen.

N-4-2c-3. Individual Setting Update Processing 3 FIG. 145 is a flowchart showing a subroutine of individual setting update processing 3 in the individual setting change processing. In the per-vehicle setting update process 3, in step S1780, the next business setting file is searched for the P machine having the largest predicted out ball number data, and in step S1782, when there are a plurality of corresponding P machines, a random number is used to determine 1 Select only one. Then
The scheduled game setting value data of the P machine selected in step S1784 is updated by "-1". For example, when the game setting value is "2", the game setting value is reduced to "1". Reducing the game setting value corresponds to increasing the expected profit for the hole (making it difficult for the customer to generate a big hit).

Next, in step S1786, the prediction data corresponding to the updated setting value is acquired from the model game setting value file, and the prediction expected profit data of the P machine is calculated.
This is a simulation of how much the predicted expected profit data of the P machine is increased by decreasing the game setting value. Then, step S17
At 88, the forecast expected profit data of all P aircraft are summed up to calculate the forecast expected profit data of the hall. Next, in step S1790, the difference between the target expected profit and the predicted expected profit is calculated, and it is determined whether or not the difference calculated in step S1792 is the minimum (is the allowable range). That is, it is determined whether or not what is aimed for as the target expected profit is simulated as the predicted expected profit.

If the difference between the target expected profit and the predicted expected profit is not the minimum in step S1792, step S17.
Proceeding to 94, the P machine having the next largest predicted out ball number value (P machine having a large number of operations) is selected, and the process returns to step S1782 to repeat the same loop. When the difference between the target expected profit and the predicted expected profit is minimized by repeating the loop, the process proceeds to step S1796, the next business setting screen data output process is performed, and the process returns to the per-unit setting change process. By performing the above processing, the data for simulating the case where the target expected profit is made larger than the predicted expected profit up to now is recalculated, and the result is displayed on the screen.

N-4-2c-4. Individual Setting Update Processing 4 FIG. 146 is a flowchart showing a subroutine of individual setting update processing 4 in the individual setting change processing. In the per-vehicle setting update processing 4, in step S1800, the next business setting file is searched for the P machine with the smallest predicted out ball number data. Select only one. Then
The scheduled game setting value data of the P machine selected in step S1804 is updated by "+1". For example, when the game setting value is "2", the game setting value is increased to "3". Increasing the game set value is equivalent to reducing the expected profit for the hole (which means that the jackpot is likely to occur for the customer).

Next, in step S1806, the prediction data corresponding to the updated setting value is acquired from the model game setting value file, and the prediction expected profit data of the P machine is calculated.
This is a simulation of how much the predicted expected profit data of the P machine becomes smaller by increasing the game setting value. Next, step S18
At 08, the forecast expected profit data of all P machines are totaled to calculate the forecast expected profit data of the hall. Next, in step S1810, the difference between the target expected profit and the predicted expected profit is calculated, and it is determined whether the difference calculated in step S1812 is the minimum (is it within the allowable range). That is, it is determined whether or not what is aimed for as the target expected profit is simulated as the predicted expected profit. If the difference between the target expected profit and the predicted expected profit is not the minimum in step S1812, step S1814.
Next, the P machine having the smallest predicted out ball number is selected, the process returns to step S1804, and the same loop is repeated. When the difference between the target expected profit and the predicted expected profit is minimized by repeating the loop, the process proceeds to step S1816, the next business setting screen data output process is performed, and the process returns to the setting change process for each vehicle. By performing the above processing, data for simulating a case where the target expected profit is made smaller than the predicted expected profit up to now is recalculated, and the result is displayed on the screen.

N-4-2d. Setting UP Processing FIG. 147 is a flowchart showing a subroutine of setting UP processing in the next business setting processing. In the setting UP processing, it is determined in step S1820 whether the menu number is "0" or "3". If the menu number is "0" or "3", it corresponds to a state where the sales amount or the expected profit is not calculated. Equivalent to. The calculation to change the game setting value of P machine is the menu number = "3"
It is. When the menu number is not "0" or "3" (otherwise), the process returns to the next business setting process. If the menu number is "0" or "3", the flow advances to step S1822 to set the menu number to "3".
Set to. As a result, the calculation for changing the game setting value of the P machine becomes possible.

[0352] Next, in step S1824, the scheduled game setting value data in the next business setting file corresponding to the P machine whose cursor is displayed on the next business setting screen (Fig. 160) is updated by "+1". For example, when the game setting value is "2", the game setting value is increased to "3". Increasing the game setting value means that the sales amount (and the expected profit) becomes smaller for the hall, while the jackpot is likely to occur for the customer. Next, in step S1826, each item data corresponding to the scheduled game setting value is acquired from the model game setting value file and stored in the next business setting file. Next, in step S1828, the data of the next business setting file is displayed on the screen. With this, it is possible to simulate how much each item data of the P machine is changed by increasing the game setting value corresponding to the operation of the “increase setting” button, and the result is displayed on the screen. Become. After step S1828, the process returns to the next business setting process.

N-4-2e. Setting DOWN Processing FIG. 148 is a flowchart showing a subroutine of setting DOWN processing in the next business setting processing. Setting DO
In the WN processing, it is determined in step S1830 whether the menu number is "0" or "3". If the menu number is "0" or "3", it corresponds to a state where the sales amount or the expected profit is not calculated. Equivalent to. The calculation for changing the game setting value of the P machine is the menu number = “3”. When the menu number is not "0" or "3" (otherwise), the process returns to the next business setting process. If the menu number is "0" or "3", the flow advances to step S1832 to set the menu number to "3". As a result, the calculation for changing the game setting value of the P machine becomes possible.

Next, in step S1834, the scheduled game setting value data in the next business setting file corresponding to the P machine whose cursor is displayed on the next business setting screen (FIG. 160) is updated by "-1". For example, when the game setting value is "2", the game setting value is reduced to "1". Reducing the game setting value means that the sales amount (and the expected profit) increases for the hall, while the jackpot is less likely to occur for the customer. Next, in step S1836, each item data corresponding to the scheduled game setting value is acquired from the model game setting value file and stored in the next business setting file. Next, in step S1838, the data of the next business setting file is displayed on the screen. As a result, it is possible to simulate how much each item data of the P machine is changed by lowering the game setting value corresponding to the operation of the “lower setting” button, and the result is displayed on the screen. Become. After step S1838, the process returns to the next business setting process.

N-4-2f. Hall Performance Calculation Processing FIG. 149 is a flowchart showing a subroutine of hall performance calculation processing in the next business setting processing. In the hall score calculation process, it is determined in step S1840 whether or not the menu number is "3". The menu number “3” corresponds to a state where the sales amount or the expected profit is not calculated. If the menu number is not "3",
Return to the next business setting process. If the menu number is "3", the flow advances to step S1842 to perform next business setting screen data output processing. As a result, the calculation for calculating the hole result data is performed in response to the operation of the “calculate hole result” button, and the result is displayed on the screen. After step S1842, the process returns to the next business setting process.

N-5. Aggregation processing 2 standby processing FIG. 150 is a flowchart showing a subroutine of aggregation processing 2 standby processing in the closing screen process. In the counting process 2 standby process, the counting screen is displayed in step S1900. Although not shown in the drawing, the counting screen is a screen for displaying a message “I am counting now!” On the screen to inform that the counting is in progress. Then
In step S1902, the aggregation monitoring timer is initialized. The aggregation monitoring timer counts the time for securing data every 1 second. Next, in step S1904, the elapsed time of the aggregation monitoring timer is acquired, and in step S1906, it is determined whether the elapsed time has reached 1 second. If it has not reached 1 second, the process returns to step S1904 and repeats the process. If it reaches 1 second, the process proceeds to step S1908 to obtain the hole operating state data from the hole day result file. Next, in step S1910, it is determined whether or not the hall operating state data is “offline”, and if it is not “offline”, the process returns to step S1902 and the process is repeated. Then, when it becomes "offline", step S19
Go to 12 and delete the totalization display screen. Step S19
After twelve, the process returns to the closing screen process.

Next, a game method of the card type game system will be described. (A) Purchase of Card First, the gaming company 1a to 1n (hereinafter represented by the reference numeral 1) purchases a card (so-called raw card) in which security data, serial number of the card, etc. are recorded from the card company 2. Then, it is set (stock) in the card issuing machine 23 before opening. The management device 11 receives information such as security data from the card company 2 and transmits it to the card issuing machine 23 as an initial value, and sets the initial value of the card issuing machine 23. On the other hand, with respect to other terminal devices, each terminal device (gaming machine 31, large amount of money addition machine 25, card renewal machine 24, prize POS 14) that requires card verification is controlled by the management device 11 every day. Information, security data,
The identification code (individual identification number) of each terminal device is sent to each terminal device to set the initial value. In this case, game store 1
Pays the card price to the card company 2 (for example, payment once at the end of the month).

Next, the player inserts money into the card and issues a raw card 400 of which the validity is judged by the card issuing machine 23 to purchase. That is, also in the card issuing machine 23, the IC card 400 and the card issuing machine 23 perform mutual authentication processing and issue. At the same time, each information of the issued card 400 is sent from the card issuing machine 23 to the management device 11, and the management device 11 secures the storage area of the card. In the state where the card is purchased, the ball lending amount of the card is 0, the accumulated ball amount is 0, and the number of balls held is 0. (B) Addition of amount of money Next, the player inserts the purchased card into the large amount of money adding machine 25 and inserts coins or bills to add a desired amount of money (up to 20,000 yen) to the card (that is, a prepaid amount of money on the card). Ask for). For example, if the amount of 10,000 yen is added, the ball lending amount becomes 10,000 yen. Also in this case, similarly, mutual authentication processing is performed between the large-sized amount addition machine 25 and the IC card 400 to add the amount, and the added amount and the like are transmitted to the management device 11 at regular intervals as operation data. In this case, the card company 2 charges the gaming shop 1 for the amount of money added to the card, while the gaming company 1 pays the card company 2 for the amount of money added to the card (for example, Settlement once at the end of the month).

(C) Start of game Next, the player inserts the card with the added amount into the game machine 31.
Play by inserting into. Also in this case, as in the case described above, mutual authentication is performed, and in a valid case, the game can be played. Briefly explaining the enclosed ball type game, the game machine 31 performs mutual authentication of the IC card 400, and based on the result, the amount of money (value information) recorded in the IC card 400 can be used for the game. The number is converted into a number (game value information) so that the game can be played, and the number of balls (game value information) already recorded as a result of the game allows the game to be played, and the result of the game is recorded in the IC card 400. Specifically, when the IC card 400 is inserted, the information (amount data, ball number data, etc.) of the IC card 400 is read to lend a ball, or the number of balls acquired by the player is calculated. The information on the ball lending (that is, sales) by the IC card 400 is exchanged between the hall management device 11 and the management analysis device 12 in the network via the optical transmission / reception unit 75 of the display unit 74. Transfer.

Explaining the specific operation of the game machine 31, here, 40 balls are enclosed inside the game machine 31 and the IC in which the amount data (value data: remaining frequency) is recorded
When the player inserts the card 400 into the card insertion slot and the player presses the ball lending switch (or the piling ball switch) on the touch panel, the number of balls the player has is increased according to the purchase frequency of the balls, and the number of balls held is displayed on the LCD The game balls that are displayed and enclosed within the range of the number of possessed balls can be launched into the game area.
And for the game played in response to the firing of the enclosed ball,
It is determined whether the game result is in a specific profit state (safe ball) or in another state (out ball), and in the case of a specific profit state, a predetermined number of prize balls (for example, 13 balls). The player's profit (the number of balls he holds) is increased in correspondence with the prize balls or seven prize balls. In addition, by collecting the game balls that have passed through the game area and guiding them to the launch position, the enclosed game balls are circulated and used for the first type of pachinko game.

Then, at the time of firing the above-mentioned enclosed sphere, LC
"1" is subtracted from the number of balls held displayed in D, and the display of the number of balls held is updated based on the result. At this time, it is determined whether or not the enclosed ball falling in the game area is a winning ball. If it is determined that the winning ball is won, the set number of winning balls (for example, 13 winning balls or 7 winning balls) is determined. ) Is added to the number of balls, and the display of the number of balls is updated based on the result. The player confirms the current number of balls held and the increase / decrease based on the numerical data of the number of balls held.
When the player tries to settle the game, the game value of the numerical data displayed as the number of balls held by pressing the end switch is set by the card reader / writer 243.
It is written in the C card 400, and the game value is received.

In the course of the game, the card information read during the game is transmitted to the management device 11, and the card information (card file information) of the card recorded on the management device 11 side and the game device 31 are transmitted. Compare with the card information that has been received. In this case, even if the comparison result (matching result) does not match, the game is enabled by only recording the history in the mismatch history file (card usage history file). That is, by using the highly secure IC card 400 and performing mutual authentication by a security system having extremely high safety using encrypted information,
This is because the information in the IC card 400 is prioritized over the similar information recorded in the management device 11 so that the game progresses quickly.

The player borrows balls within the range of the balance of the ball lending amount (value of value) and converts them into the number of balls owned (game value) to play the game. The number of balls obtained as a result of the game is added to the number of balls held and recorded on the card. In the gaming machine 31, it is possible to lend a ball even within the range of the amount of stored coins. That is, in the prize POS 14, the number of coins held can be exchanged for the accumulated coin amount at a predetermined exchange rate. During the game, the ball lending amount and the stored ball amount are automatically subtracted by the ball lending operation within these ranges. In addition, the number of possessed balls is automatically increased / decreased during the game. In this case, the amusement store 1 requests the card company 2 for the ball lending amount by the card (including the ball lending by the stored amount), while the card company 2 makes a ball lending to the amusement store 1 using the card. The amount of money will be paid (for example, settlement once a day).

(D) Game interruption When the interruption switch arranged on the gaming machine is pressed during the game, the game can be temporarily suspended. For example, the game is interrupted when going to a meal or a toilet. (E) End of game To end the game, press the end switch arranged on the gaming machine. As a result, the gaming machine stand number (gaming machine address) and ball information are newly recorded on the card, and each card information is sent to and stored in the management device 11. At this time, the information added to the card includes a final hole name, a final hole number, a game machine number record, a ball lending amount, and the number of balls owned. For example, the card ball lending amount = 7
It is stored such as 000 yen, the accumulated amount of coins = 0, and the number of balls owned = 2110. When the game is over, the player moves to another machine or pays for it.

(F) Moving When moving to another table after the game is finished, if the IC card 400 is held, it can be moved to another table as it is.
It should be noted that it is possible to move to another table as it is only in the shop and on the day, and in a state in which the business is in line with the business of the hall (for example, a business mode in which the business can be moved instead of being replaced once). (G) Settlement In the case of settlement, the player inserts the card into the prize POS 14 and selects exchange with cash according to a predetermined exchange rate, exchange with a prize, or exchange with a coin amount according to a predetermined exchange rate,
Perform the desired form of exchange. Even in the prize POS 14,
Mutual authentication and information transfer are performed as described above. In addition, the player who has completed the settlement can return to the game machine 31 and play a game. (H) Other stores The number of balls owned by a player who has completed settlement at our store is 0,
All are converted into valuable value such as ball lending amount or accumulated ball amount, so it is possible to go to another store and play games.
This is because only our shop can use the number of balls.

Next, the procedure for viewing the business information including the business forecast information of the business analysis apparatus 12 by executing the above programs will be specifically described with reference to the screen of the business analysis apparatus 12. (A) Main Screen When the management analysis device 12 is powered on and logged in to the management analysis system, the main screen of the management analysis system as shown in FIG. 151 appears on the entire screen of the display device 160. On the main screen, today's date and hall name are displayed, and today's event is also displayed in text information. In addition, various buttons that can display sub screens (for example,
"Hall", "Model", "Customer", "Labor", ...
"Settings", ...) is displayed on the screen. in this case,
"Hole" button is for analyzing hall data, displaying screens, etc.
The "Model" button displays information about the model, such as "Customer"
The button corresponds to the display of customer information, and the “setting” button corresponds to registration of model information. Furthermore, a plurality of "option" buttons are arranged at the bottom of the screen, and an "end" button for terminating the system is arranged.

(B) Screen selection by button When each button displayed on the main screen is pressed, important information regarding hall sales can be viewed. For example, when the "hole" button is pressed, a new window is created and a hall information screen is displayed (not shown). That is, the hall information screen is displayed on the front side of the main screen in a multi-window manner. You can open multiple such screens, and even display the one you want to see at the top. And, except when the data is collected after the store is closed, these screens can be viewed even during the hall operation. Here, if you press the "Settings" button displayed on the main screen,
The setting screen shown at 52 appears in a multi-window overlapping the front side of the main screen. On the setting screen, "model setting", "installation confirmation" and "end" buttons are displayed. By pressing the "model setting" button, the model of the gaming machine installed in the hall is set as the management data of the management analyzer 12. This is done by reading the model installed in our store from the model registration file and storing it in a necessary file (for example, model information file). If you press the "Confirm Installation" button, you can confirm the installation information that was installed in the hall and stored in a file as data. The "end" button is used to erase the setting screen and bring the main screen back to the front side.

(C) Screen during opening of hall During opening of a hole, two screens automatically appear (hole performance prediction screen and game stand operation screen). As shown in FIG. 153, the hall result prediction screen displays the predicted value of today's business performance, and the game machine operation screen displays operation information of each machine by selecting the model. Both screens display information in real time, and the screen continues to be displayed until the store is closed. FIG. 154
(A) has shown the state in which the hall-results prediction screen and the game stand operation screen were overlapped on the front side of the main screen. As shown in FIG. 153, the hall performance prediction screen (management prediction information display screen) displays today's date, day of the week, event contents, opening time, planned closing time, and hall name in the upper area of the screen. In this case, the "event" is displayed with the following contents.・ Normal business condition of our store ・ Self-replacement Business condition when we replace the units at our store (new unit replacement) ・ Other replacement Business condition when we replace the units at another store (new unit replacement) ・ Half-day And, half of the stores are closed and the other half are open

Further, the current time is displayed and updated in real time. In the area on the right side of the screen, the current sales amount, profit, number of visitors, number of out balls,
The number of safe balls, the number of premium balls added, the number of bonus balls, the amount converted, and the amount stored are displayed in real time, and the predicted value of each data at the time of closing is displayed, and each predicted value data is constantly recalculated for 1 minute. The display is updated every time. Line graphs corresponding to sales amount and profit are displayed in the left side area of the screen, and these graphs are similarly updated every minute. In the line graph, the solid line shows the measured value and the broken line shows the predicted value. As described above, on the hall performance prediction screen, in addition to the prediction information, information such as overall sales and profits as of the day that is desired to be grasped in real time in management is displayed. Also, on the hall performance forecast screen, the forecast information of the day can be viewed together, and important sales information for the manager can be obtained. In addition,
The hall result prediction screen is not erased by the operation of the operator, the menu selected by mistake is not erased, and the operation can be entrusted to beginners with peace of mind.

(D) Gaming table operating screen The gaming table operating screen is an input screen for selecting operating information on the day, and the operating information for the day is displayed by the operating screen for each model, and the operating screen for each model is for operating all halls. Display data in real time. Figure 1 is the first screen of the game console operation screen.
54 (b), a plurality of models (for example, model A to
A model button for selecting a desired model from E) is displayed. When any one of the model buttons is pressed, one operating screen for each model is popped up and displayed as shown in FIG. 155 (a). Also, if you press multiple model buttons,
As shown in (b), a plurality of model-specific operation screens are displayed in cascade. FIG. 156 shows an example of the contents of the model-specific operation screen, in which the operation data of all the machines belonging to the model (here, model A) are displayed in a table format in real time. However, since it is not possible to display all the units on the screen, the scroll bar is used for scroll display. On the model-specific operation screen, when a big hit occurs, the line of the corresponding unit (for example, the 102nd) blinks in red. When the "Close" button is pressed on the model-specific operation screen, the model-specific operation screen is closed.

Here, the gaming table operating screen is displayed in a multi-window manner on the front side of the main screen. In this case, the main screen, the hall performance prediction screen, and the gaming table operation screen are continuously displayed on the display device 160,
It is always in the display standby state for multiple pieces of operation information. In particular, the gaming table operating screen cannot be erased by the operation of the operator, and the process of the gaming table operating screen is activated by the opening packet from the management device 11 and stopped by the closing packet. Then, when the "end" button is pressed on the main screen (Fig. 151), the gaming table operation screen shown in Fig. 154 is also ended, and the management analyzer 12 is shut down.

As described above, the fact that it is always in the standby state for displaying a plurality of operation information means that the main screen is
Information collection is performed by multitasking in a state where the hall result prediction screen and the game stand operation screen are continuously displayed, and the operation information calculated on the screen of the display device 160 and the information collection process of the terminal device is displayed. And the process of doing it at the same time. Therefore, unless the menu screen becomes the basic screen and the "end" button is operated, it is possible to always reside and input the selection information for displaying the accumulated operation information of the terminal device. As the accumulated operation information, for example, a hall information screen for displaying game information, sales, profits, etc. of all the gaming machines from the day before in the past one week, and hall data for the past three months are analyzed and simulated. There is a hall data analysis screen shown by a three-dimensional graphic image, a customer information screen for displaying information about the customer such as the customer's record, the number of customers visiting the customer, and the customer retention status.

Therefore, the operation for selecting desired information from the enormous amount of operation information can be easily performed through the menu screen which is always resident. In addition, as the selection input of operating information on the day is performed on the game console operating image, and the selection input of accumulated operating information is performed on the menu screen, these game console operating images and menu screens are grouped and displayed on the screen. The operation for selecting information required by a person is easy. Furthermore, the game console operation screen for selecting the operation information on the day is not erased by the operation of the operator, and the selected menu is not erased by mistake, and the operation can be entrusted to the beginner with peace of mind.

(E) Appearance of interrupt event screen The interrupt event screen appears when there is a call from the gaming machine during business hours and when an error occurs in the gaming machine. (E-1) Call from gaming machine When there is a call from the gaming table during business (for example, when the customer operates a call switch to call a clerk on the gaming machine), as shown in FIG. With the hall result prediction screen and the game table operation screen displayed in a superimposed manner on the front side of the screen, the interrupt event screen is further activated and appears in the foreground. The interrupt event screen in this case is
As shown in FIG. 158 (a), the caller's machine number (for example, the 103's) is displayed and a message "You are calling" is displayed. An icon is displayed below the interrupt event screen. Therefore, it is easy to recognize the event of calling from the gaming machine, and it is possible to easily identify the gaming machine.
The state change of the gaming machine can be grasped promptly.

(E-2) Error Occurring in Gaming Machine If an error occurs in the gaming table during business (for example, if a ball clogging error occurs in the gaming machine), FIG.
As shown in (a), the interrupt event screen is activated and appears in the foreground while the hall result prediction screen and the game stand operation screen are displayed on the front side of the main screen. The interrupt event screen in this case is shown in FIG. 158 (b).
As shown in, while displaying the number of the source of the error (for example, the 107's), the message "Open the ball clogging error occurrence panel and remove the balls" is displayed. An icon is displayed below the interrupt event screen. Therefore, it is easy to recognize the event that an error has occurred in the gaming machine, the gaming machine can be easily identified, and the state change of the gaming machine can be quickly grasped.

(F) Erasing the interrupt event screen The interrupt event screen is erased when an event that has occurred in the gaming machine is canceled, and when an icon is created (in the case of being iconified by an operation and automatically. Including the case of being iconized). (F-1) Releasing Event Occurring in Gaming Machine When the call from the gaming machine is canceled (for example, when the calling switch of the gaming machine is turned off), the interrupt event screen automatically closes and disappears. Thereby, the manager can easily recognize the phenomenon that the call from the gaming machine has been canceled while monitoring the screen, and can quickly grasp the change in the state of the gaming machine. Similarly, when the error of the gaming table is resolved (for example, when a ball jam error occurs, the panel is opened to remove the ball), the interrupt event screen is automatically deleted. Thereby, the manager can easily recognize the phenomenon that the error of the gaming machine has been resolved by monitoring the screen, and can quickly grasp the change in the state of the gaming machine.

(F-2) In the case of being iconized by operation When the interrupt event screen appears, the manager recognizes a call from the gaming machine or an error occurs, but when the manager subsequently presses the icon (for example, , Click),
The interrupt event screen shown in FIG. 158 (a) or 158 (b) is iconized (becomes a marker state), and as shown in FIG. 157 (b), an event occurrence is displayed below the gaming table operation screen. The display is moved to the position corresponding to the order, and the interrupt event screen is deleted. Then, when the event that occurred in the gaming machine in this state is resolved, the icon mark (see FIG. 157 (b)) of the corresponding table is erased.

(F-3) In the case of being automatically iconified (when the occurrence events of the gaming machine are continuous) The interrupt event screen appears, and before the iconification operation is performed, the game continues. When an event such as a call from the machine or the occurrence of an error occurs, the interrupt event screen that has appeared until then is automatically converted into an icon, and FIG.
As shown in FIG. 7 (b), the interruption event screen is erased by moving and displaying it at the position corresponding to the order of event occurrence below the gaming table operation screen. Then, the interrupt event screen corresponding to the latest occurrence event appears. Similarly, after that, if the occurrence events of the gaming machine continue, only one interrupt event screen corresponding to the latest occurrence event appears, and the interrupt event screens corresponding to the previous occurrence events are deleted one after another and the icon And is moved and displayed at the position corresponding to the order of event occurrence below the gaming table operation screen. As a result, the manager is monitoring the screen, and when events such as a call from the gaming machine or an error occurrence occur continuously, only the latest event is displayed on the interrupt event screen, and the previous events are Since the icons are displayed and moved to a position corresponding to the order of event occurrence, the events occurring in the gaming machine can be sequentially and easily recognized, and the state change of the gaming machine can be quickly grasped.

(G) Weather Input Screen Next, when the hall is closed, the hall performance prediction screen and the game table operation screen are closed, and a weather input screen as shown in FIG. 159 appears. On the weather input screen, a message "Please input today's weather" is displayed, and buttons for inputting "clear", "cloudy", "rain", and "snow" are displayed. Also, the message "Please enter the weather for the next business day" is displayed on the same screen, and in addition to the buttons for entering "fine", "cloudy", "rain" and "snow", "weather The "Ignore" button is displayed. The "Ignore Weather" button is to ignore the weather in the data prediction of the next business day. Pressing any weather button today or on the next business day will change the color of the button and then press the "Confirm" button to enter the weather. When the weather is entered, the data is totaled and the totaling display screen is displayed during the totalization of the data. At this time, in the data prediction of the next business day, the calculation is performed in consideration of the weather, and the prediction accuracy of the data is improved.

(H) Next Business Setting Screen When the data collection is completed, the business data editing process is performed after the store is closed and the next business setting screen (FIG. 160) appears. On the next business setting screen, the hall performance prediction data for the next business day is displayed, and for example, the predicted value of each item of sales amount, profit, occupancy rate, and number of people visiting the store is displayed. At this time, when the data change button is pressed, the sales amount and the profit are recalculated and displayed in order to predict the increase or decrease of those values. Here, the next business setting screen (FIG. 160) corresponds to a forecast information change input screen for inputting change information of forecast sales information or forecast profit information. In addition, the next business setting screen has an area for setting each unit, and the unit setting area displays the unit number, model name, estimated operating number (out ball number), game setting value, and all holes You can see the forecast data of the stand. It should be noted that a scroll bar is arranged in the setting area for each table, and it is possible to display a table that does not appear on the screen.

Further, on the next sales setting screen, the buttons of “change setting by unit”, “increase setting”, “decrease setting”, “calculate hall results”, “end & adjust stand”, and “return” are displayed. The detailed data can be changed by operating these buttons. Here, the setting area for each machine on the next business setting screen corresponds to a game machine setting information information change input screen for inputting change information of the game machine setting information for changing the game machine setting information. If you press the "Change settings for each machine" button, you can specify the gaming machine for each machine and change the setting value. At this time, if you specify the machine number and press the "Increase setting" button, If the "decrease setting" button is pressed, the setting value of the table is changed to be decreased and the data is recalculated and displayed. When the "calculate hole score" button is pressed, the predicted data of hole score is calculated and displayed. When you press the "End & stand adjustment" button, the stand adjustment confirmation screen appears. When the "Return" button is pressed, each data of the next business setting screen is returned to the original value (the value immediately after the same screen is displayed before the data is changed) and displayed.

(I) Platform adjustment confirmation screen When the "End & platform adjustment" button is pressed on the next business setting screen,
The platform adjustment confirmation screen shown in FIG. 161 appears. On the platform adjustment confirmation screen, you can select the platform adjustment item,
The message “Please select the item for platform adjustment” is displayed. When you select an item, an attention mark is displayed at that location. When five items are selected and the "execute" button is pressed, table adjustment data for nail adjustment is transferred to all gaming machines (specifically, all display units 74). FIG. 161 shows an example in which the number of out balls, the base value, the number of special prizes, the operating time, and the special prize probability are selected as the machine adjustment items. The platform adjustment items can be set / released freely. When the "Cancel" button is pressed, the selection of the base adjustment item is canceled.

(J) Adjustment of game machine based on machine adjustment data When the machine adjustment data is transferred to the display units 74 of all the game machines by pressing the "execute" button on the machine adjustment confirmation screen, the display units 74 of all the machines are displayed. Each platform adjustment data is displayed. . FIG. 162 is a specific example showing platform adjustment data displayed on the 102-series display units 74. As shown in FIG. 162 (a), the number of out balls, the base value, the number of special prizes, the operating time, and the special prize probability as the base adjustment data are displayed separately in the lines of the last result, the same day setting, the same day result, and the next setting There is. The unit of the number of out balls is a numerical value × 10, for example, 1232 means 12320. The unit of the base value is 1/1000 [%], for example, the base value = 3
The value of 86 means 38.6%. The number of special prizes is the number of times a big hit occurs. The unit of the operating time is a numerical value × 10 seconds, for example, 3580 seconds. The special prize probability is the probability of big hit occurrence, and for example, 247 means that big hit probability = 1/247.

The previous result is the result data of the previous business day, the current day setting is the setting data for the current business day, the current day result is the result data of the current business day, and the next setting is the setting data for the next business day. That is. The manager of the hall performs nail adjustment and probability setting of the table while viewing the table adjustment data displayed on the display unit 74. Therefore, it is possible to extremely easily and efficiently perform nail adjustment and probability setting of the gaming machine. Moreover, even an inexperienced manager can easily perform nail adjustment and probability setting. Further, the probability can also be set in the management device 11 using the automatic setting file.

As shown in FIG. 162 (b), the 102-series display units 74 have the 102-series left and right gaming machines (one of the right or left gaming machines at the end of the island facility). ) About the platform adjustment data and the model average data of the model to which the platform belongs (data calculated by actual measurement data) are displayed at the same time. Therefore, the manager can also check the platform adjustment data of the left and right game machines that are installed side by side, and can perform well-balanced platform adjustment in consideration of the left and right platforms. In addition, model average data can be confirmed, and platform adjustment can be performed in a well-balanced manner in a row of islands where gaming machines of the same model are arranged. The table adjustment data displayed on the display unit 74 is shown in FIG.
Although it may be numerical data as shown in FIG. 16, for example, as shown in FIG. 163, the table adjustment data of the table may be displayed in a two-dimensional graph. As the machine adjustment data, four data such as the sales of the machine, the base value, the number of special prizes, and the operating time are displayed. In this case, the platform adjustment data of the platform is displayed as a solid line, and the model average data is displayed as a broken line. By doing so, it is possible to visually recognize the sales of the machine, the base value, the number of special prizes, and the operating time in a graph at a glance, and it is possible to easily perform the machine adjustment in consideration of the balance with the model average.

Next, when the transfer of the stand adjustment data is completed at the time of closing the store, the totalization display screen is erased at the time of going offline after 1 second has passed in the totaling process 2 waiting process, and the closing screen process ends. Then, when there is an instruction to terminate the system, all the processes are terminated and the apparatus is shut down. The power is turned off manually by the management. Note that FIG.
The system also ends when the "end" button is pressed on the main screen of the management analysis system shown in 1.

As described above, in this embodiment, the management analysis system 1
The data from the terminal device is collected and aggregated by 2
When the data aggregation is completed, the business data editing process is performed after the store is closed and the next business setting screen (FIG. 160) is displayed.
Then, on the next sales setting screen, the hall performance prediction data for the next business day is displayed, and the predicted values for each item of sales amount, profit, occupancy rate, and number of people visiting the store are displayed. At this time, the sales amount,
In the calculation of the predicted value of profits, etc., the predicted number of people visiting the store is calculated by the process for predicting the number of people visiting the store on the next business day shown in FIG. 89, and then the hole out for the past month by the process for predicting the number of halls operating on the next business day shown in FIG. 91. In addition to calculating the average number of visitors to the number of balls, the predicted number of visitors to the store is added up to calculate the predicted number of balls, and then the total number of outs for the past 14 days is calculated by the next-business-day-operation-number-of-operations prediction process shown in FIG. The ratio of the number of balls and the number of out-balls for each model (operating occupancy ratio) is calculated, and the operating occupancy ratio for each model on the next day is calculated using the least squares method, and the operating occupancy ratio for each model and the above are calculated. The predicted out ball number is added up to obtain the predicted out ball number for each model. Then, the predicted number of out-balls for each model is divided by the number of game machines of the corresponding model to be the predicted number of out-balls for each game machine. In addition, the predicted number of people visiting the store, the predicted number of balls out of the hall,
The predicted number of out-balls for each gaming machine is used as the basic information necessary for prediction. Next, by the next business setting screen data output process shown in FIG. 138, the predicted out ball number for each gaming machine, model rule set value file information (predicted winning ball game rate), model game set value file information (base, jackpot probability, etc.) From this, the forecast profit and forecast sales are calculated. Then, the forecast profit and forecast sales calculated in this way are displayed on the screen and presented to the manager.

Therefore, the following effects can be obtained. (1) It is possible to effectively utilize the game information from the increased and complicated terminal devices to perform arithmetic processing, and provide management forecast information such as sales and profits of the game hall to the manager as concrete data. As a result, it is possible to utilize the forecast information provided as concrete data for the management of the hall. Especially, the effect is remarkable for a manager who has little management experience. Unlike conventional methods that aim for target profits etc. according to empirical rules, management forecast information is provided as concrete data by detailed simulation, so you can see what kind of results you actually approach even without doing business. The prediction can be performed with high accuracy (rather than the conventional sensory prediction), and the reliability can be improved. (2) By displaying the predicted number of people visiting the store on the screen, it is possible to know the number of people visiting the store that is most relevant to sales and profit by highly accurate simulation. (3) By calculating and displaying the predicted operating rate of the gaming machine (predicted gaming machine operating rate information) from the predicted number of out-balls, business hours (planned calendar file information), and installed machine number information Can provide a wealth of information.

(4) When the data change button is pressed to input changes in the sales and profit forecasts, the data is recalculated and displayed to predict the increase or decrease in sales and profits. Alternatively, the forecast profit or forecast profit is changed by changing and inputting the forecast profit and changing the gaming machine setting information (probability setting value) associated with the gaming machine based on the forecast profit or forecast profit changed. By calculating and displaying a value (probability setting value) that is close to, if the setting value of the gaming machine is adjusted to the provided setting value, it is more approximate to the target value of sales and profit than the setting adjustment based on the empirical rule. Let me do planned sales. In addition, the operation itself is extremely easy because the management only needs to change and input sales and profit information that the manager wants to know (that is, operability is good).

(5) Press the "Change settings for each machine" button, specify the gaming machine by machine, and change the setting value. By specifying the machine number, you can increase the setting value of the machine. Recalculate forecast sales and forecast profit data,
By changing the setting value of the table to lower and recalculating the same data and displaying it, that is, changing and inputting the gaming machine setting information (probability setting value) associated with the gaming machine By recalculating the next forecast sales and forecast profits based on the gaming machine setting information and the predicted number of out-balls for each gaming machine, that is, sales by allowing the manager to change and input the setting values of the gaming machine, By simulating and displaying the profit, the setting of the gaming machine customized by the manager can be freely changed based on a certain target value (sales, profit). That is, it is possible to extremely easily operate the method of adjusting the set value of the gaming machine in order to bring it close to the target profit of the next day business. For example, in order to get close to the target profit of the next day's business, etc., the manager can change the information value by his / her own will and calculate the profit etc. The analysis device 12 can be obtained. As a result, precise and planned sales can be easily performed. (6) The game analyzer setting information (probability set value) set by the management analyzer 11 by connecting the management analyzer 12 to the management device 11
Or the gaming machine setting information (probability setting value) whose settings have been changed
To the management device 11 (specifically, the management analysis device 12 sends the setting value file to the management device 11),
The management device 11 can send the game machine setting information (information in the setting value file: probability setting value) to the corresponding game machine as an initial value on the next day (next business day), and the management machine 12 sets the game machine settings. Information (probability set value) can be automatically set for each gaming machine.

The embodiment of the present invention is not limited to the above embodiment, but various modifications as described below are possible. (A) It can be applied to pachislot machines. (B) The present invention is applicable not only to pachinko gaming machines but also to, for example, video game machines. (C) The gaming machine is not limited to the enclosed ball type, and any type of gaming machine can be used as long as the information can be collected by the management analysis apparatus 12 and the setting information of the gaming machine can be changed by the management analysis apparatus 12. It may be a type of gaming machine. (D) The configuration for collecting the information from the gaming machine is not limited to the example using the network as in the above embodiment, and the information from the gaming machine may be collected in any configuration.

(E) The present invention is an example of application to a management analysis device as an information processing device in a game arcade, but it is an information processing device in a game arcade and collects information of a plurality of terminal devices and collects the information. The information processing device is not limited to the business analysis device as long as it is an information processing device that predictively notifies management information. For example, the management device of the game arcade may collect the information of the terminal device and perform the prediction notification of the management information, or a dedicated device that collects the information of the terminal device and performs the prediction notification of the management information. May be provided. Alternatively, a device mainly used for other purposes may be provided with a function of collecting information of the terminal device and predicting and notifying management information. Further, both the pachi-slot gaming machine and the pachinko gaming machine may collect and inform the information thereof by one information processing device. (F) The present invention collects information from the terminal device and predictively notifies the management information, and the information from the terminal device in that case is not limited to the game-related information shown in the above embodiment. Any information may be used as long as it is desired by the manager in the information of the terminal device. (G) In the prediction notification of the management information in the information processing device of the game arcade of the present invention, the information for predicting the management information is notified on the screen, but even if the prediction of the management information is notified in combination with the voice and the sound effect. Good. Further, the screen configuration is not limited to the example as in the above-mentioned embodiment, and may be any prediction information notification screen within the scope of the object of the present invention.

[0393]

【The invention's effect】

(1) According to the first and second aspects of the invention, information from the terminal device in the game arcade is collected by the information processing device in the game arcade (for example, the management analysis device), and the predicted number of people visiting the store from the collected information, Predicted total used game value information for the next game center and predicted total used game value information for each next game machine are calculated, and based on the information including the game machine setting information, next forecast sales information and predicted profit information Is calculated and displayed, the following effects can be obtained. It is possible to effectively use the increased and complicated game information from the terminal device to perform arithmetic processing, and to provide management forecast information such as sales and profit of the game hall to the manager as concrete data. As a result, it is possible to utilize the forecast information provided as concrete data for the management of the hall. Especially, the effect is remarkable for a manager who has little management experience. Unlike conventional methods that aim for target profits etc. according to empirical rules,
Management forecast information is provided as detailed data by detailed simulation, so even if you do not do business,
It is possible to predict with high accuracy what kind of results will actually be approached (rather than the conventional sensory prediction),
Reliability can be improved.

(2) According to the third aspect of the present invention, by displaying the calculated predicted visitor number information, it is possible to know the visitor number most relevant to sales and profit by highly accurate simulation. (3) According to the invention of claim 4, the predicted operating rate of the gaming machine is based on the predicted total used game value information (for example, predicted number of out-of-balls), business hours information, and installed machine number information. A wealth of information can be provided by computing and displaying the information.

(4) According to the invention described in claim 5, the forecast sales information or the forecast profit information is changed and input, and the forecast sales information or the forecast profit information is associated with the game machine based on the changed forecast sales information or the forecast profit information. The game provided by calculating and displaying a value (for example, probability setting value) that approximates the changed predicted sales information or predicted profit information by changing the gaming machine setting information (for example, probability setting value) If the setting of the gaming machine is adjusted in the machine setting information, it is possible to carry out planned sales by making it closer to the target values of the forecast sales information and the forecast profit information than the setting adjustment based on the rule of thumb. Further, the operation itself is extremely easy because the manager simply changes and inputs the forecast sales and forecast profit information that he / she wants to know (that is, the operability can be improved).

(5) According to the invention of claim 6, the game machine setting information (eg probability setting value) associated with the game machine is changed and input, and the changed game machine setting information,
By recalculating the next predicted sales information and predicted profit information based on the predicted used game value information for each gaming machine, the setting information of the gaming machine customized by the manager can be set to a certain target value (for example, a predicted value). Sales, forecast profit) can be changed freely. That is, it is possible to extremely easily operate the method of adjusting the setting information of the gaming machine in order to bring it close to the target profit of the next day business. For example,
In order to approach the target profit of the next day's business, etc., the manager can change the game machine setting information by himself and calculate the forecast profit etc. by trial and error, and the operability is very good. An information processing device can be obtained. As a result, precise and planned sales can be easily performed. (6) According to the invention of claim 7, the information processing apparatus is connected to the management apparatus, and the gaming machine setting information (for example, probability setting value) set by the information processing apparatus or the changed gaming machine setting information is displayed. By transferring to the management device, the management device can transmit the game machine setting information to the corresponding game machine as an initial value on the next day (next business day), and the information processing device can transmit the game machine setting information to each game machine. Can be set automatically.

[Brief description of drawings]

FIG. 1 is a block diagram showing an embodiment of a game arcade facility to which an information processing apparatus according to the present invention is applied.

FIG. 2 is a diagram showing a management system of the game arcade of the embodiment.

FIG. 3 is a diagram showing a communication system of the terminal device of the embodiment.

FIG. 4 is a block diagram showing a configuration of a business analysis apparatus of the same embodiment.

FIG. 5 is a diagram showing a detailed block configuration of the business analysis apparatus of the embodiment.

FIG. 6 is a diagram illustrating a POS connection file according to the same embodiment.

FIG. 7 is a diagram illustrating a large-sized machine connection file according to the embodiment.

FIG. 8 is a diagram illustrating an issuer connection file of the same embodiment.

FIG. 9 is a diagram illustrating an updater connection file of the same embodiment.

FIG. 10 is a diagram illustrating a model registration file of the same embodiment.

FIG. 11 is a diagram illustrating a model information file of the same embodiment.

FIG. 12 is a diagram illustrating a model game setting value file of the same embodiment.

FIG. 13 is a diagram illustrating a model rule setting value file of the same embodiment.

FIG. 14 is a diagram illustrating a model layout file of the same embodiment.

FIG. 15 is a diagram illustrating a hole initial value file of the embodiment.

FIG. 16 is a diagram illustrating an inter-vehicle addition history file of the same embodiment.

FIG. 17 is a diagram illustrating an amount addition history file of the embodiment.

FIG. 18 is a diagram illustrating a settlement history file of the example.

FIG. 19 is a diagram illustrating an issuance history file of the same embodiment.

FIG. 20 is a diagram illustrating an update history file of the same embodiment.

FIG. 21 is a diagram illustrating an automatic setting file according to the same embodiment.

FIG. 22 is a diagram illustrating a P-machine same day result file of the same example;

FIG. 23 is a diagram illustrating a hole day result file of the example.

FIG. 24 is a diagram illustrating a customer same day result file according to the embodiment.

FIG. 25 is a diagram illustrating a P machine basic file of the embodiment.

FIG. 26 is a diagram illustrating a P machine result file of the same embodiment.

FIG. 27 is a diagram illustrating a P machine time series result file of the same embodiment.

FIG. 28 is a diagram illustrating a model result file according to the same embodiment.

FIG. 29 is a diagram illustrating a model time series result file of the same example.

FIG. 30 is a diagram illustrating a POS score file of the same example.

FIG. 31 is a diagram illustrating a large machine performance file of the same embodiment.

FIG. 32 is a diagram illustrating an issue machine result file of the same example.

FIG. 33 is a diagram illustrating an update machine result file according to the same embodiment.

FIG. 34 is a diagram illustrating a POS time-series result file of the same example.

FIG. 35 is a view for explaining a large machine time series result file of the embodiment.

FIG. 36 is a diagram illustrating a hole date / time series result file of the example.

FIG. 37 is a diagram illustrating a hall result file of the example.

FIG. 38 is a diagram illustrating a hall time-series result file of the same example.

FIG. 39 is a diagram illustrating a scheduled calendar file of the same example.

FIG. 40 is a diagram illustrating a practical calendar file of the same example.

FIG. 41 is a diagram illustrating a hall performance prediction file of the embodiment.

FIG. 42 is a diagram illustrating a hall time-series performance prediction file of the same example.

FIG. 43 is a diagram illustrating a P machine performance prediction file of the same embodiment.

FIG. 44 is a diagram illustrating a customer record file of the example.

FIG. 45 is a diagram illustrating a time series unit time file of the embodiment.

FIG. 46 is a diagram illustrating a remote controller history file of the same embodiment.

FIG. 47 is a diagram illustrating a P-machine detailed error registration file of the same embodiment.

FIG. 48 is a diagram showing the contents of a P-machine detailed error registration file of the same embodiment.

FIG. 49 is a diagram for explaining a next business setting file of the embodiment.

FIG. 50 is a diagram illustrating a hall score virtual file of the example.

FIG. 51 is a diagram illustrating a table adjustment item file according to the same embodiment.

FIG. 52 is a diagram illustrating a platform adjustment data file of the same example.

FIG. 53 is a flowchart showing a main program of the business analysis apparatus of the embodiment.

FIG. 54 is a flowchart showing a main screen process of the same example.

FIG. 55 is a flowchart showing a data collection process of the same example.

FIG. 56 is a flowchart showing a subroutine of offline processing of the same embodiment.

FIG. 57 is a flowchart showing a subroutine of opening preparation processing of the embodiment.

FIG. 58 is a flowchart showing a subroutine of a store opening waiting process of the embodiment.

FIG. 59 is a flow chart showing a subroutine of processing during business of the embodiment.

FIG. 60 is a flowchart showing a subroutine of initialization processing of processing during business of the embodiment.

FIG. 61 is a flowchart showing a subroutine of firing data collection processing of the embodiment.

FIG. 62 is a flowchart showing a subroutine of collected data collection processing of the embodiment.

FIG. 63 is a flowchart showing a subroutine of winning data collection processing of the embodiment.

FIG. 64 is a flowchart showing a subroutine of remote control data collection processing of the embodiment.

FIG. 65 is a flowchart showing a subroutine of bonus ball data update processing of the embodiment.

FIG. 66 is a flowchart showing a subroutine of board information data collection processing of the embodiment.

FIG. 67 is a flowchart showing a subroutine of analysis data collection processing of the embodiment.

FIG. 68 is a flowchart showing a subroutine of call information reception processing of the embodiment.

FIG. 69 is a diagram illustrating an interrupt event monitoring area according to the embodiment.

FIG. 70 is a flowchart showing a subroutine of error information acceptance processing of the embodiment.

71 is a flow chart showing a subroutine of constant time processing of the embodiment. FIG.

72 is a flowchart showing a subroutine of P machine basic file update processing 1 of the embodiment. FIG.

FIG. 73 is a flowchart showing a subroutine of game start data collection processing in the embodiment.

FIG. 74 is a flowchart showing a subroutine of game end data collection processing in the same embodiment.

75 is a flow chart showing a subroutine of P machine basic file update processing 2 of the embodiment. FIG.

FIG. 76 is a flowchart showing a subroutine of ball lending usage data collection processing of the embodiment.

FIG. 77 is a flowchart showing a subroutine of a stored coin usage data collection process according to the embodiment.

FIG. 78 is a flowchart showing a subroutine of final processing of processing during business of the embodiment.

FIG. 79 is a flow chart showing a subroutine of shop closing confirmation processing of the embodiment.

FIG. 80 is a flowchart showing a subroutine of totaling processing 1 of the embodiment.

FIG. 81 is a flowchart showing a subroutine of practical calendar file update processing of the embodiment.

FIG. 82 is a flowchart showing a subroutine of P machine result file update processing of the embodiment.

FIG. 83 is a flowchart showing a subroutine of a model result file update process of the same example.

FIG. 84 is a flowchart showing a subroutine of POS result file update processing of the embodiment.

FIG. 85 is a flowchart showing a subroutine of a large machine result file update process of the embodiment.

FIG. 86 is a flowchart showing a subroutine of issuing machine result file update processing of the embodiment.

FIG. 87 is a flowchart showing a subroutine of updating machine result file update processing of the embodiment.

88 is a flow chart showing a subroutine of hole score file update processing of the embodiment. FIG.

FIG. 89 is a flowchart showing a subroutine of a next business day visitor prediction processing of the embodiment.

FIG. 90 is a diagram showing an example of prediction of the number of people visiting a store on the next business day according to the embodiment.

FIG. 91 is a flowchart showing a subroutine of next-business-day hall operation number prediction processing of the embodiment.

FIG. 92 is a flowchart showing a subroutine of next-business-day-by-business-day number-of-operations forecasting processing of the embodiment.

FIG. 93 is a flowchart showing a subroutine of post-closing business processing of the embodiment.

FIG. 94 is a flow chart showing a subroutine of platform adjustment data transfer processing of the embodiment.

FIG. 95 is a flowchart showing a subroutine of platform adjustment data file creation processing of the embodiment.

FIG. 96 is a flowchart showing a subroutine of totaling processing 2 of the embodiment.

FIG. 97 is a flowchart showing a subroutine of automatic setting file creation processing of the embodiment.

FIG. 98 is a flowchart showing a subroutine of P machine time series result file update processing of the embodiment.

FIG. 99 is a flowchart showing a subroutine of model time series result file update processing of the embodiment.

FIG. 100 is a flowchart showing a subroutine of POS time-series result file update processing of the embodiment.

FIG. 101 is a flowchart showing a subroutine of a large machine time series result file update process of the embodiment.

FIG. 102 is a flowchart showing a subroutine of hole time-series result file update processing of the embodiment.

FIG. 103 is a flowchart showing a subroutine of hole score prediction file update processing of the embodiment.

FIG. 104 is a flowchart showing a subroutine of hole time-series performance prediction file update processing of the embodiment.

FIG. 105 is a flowchart showing a subroutine of hall time-series predicted sales amount data creation processing of the embodiment.

FIG. 106 is a flowchart showing a subroutine of a hole time-series predicted out-ball-number data creation process of the embodiment.

FIG. 107 is a flowchart showing a subroutine of hole time series prediction safe ball number data creation processing of the embodiment.

FIG. 108 is a flowchart showing a subroutine of a time-series predicted number of people visiting a store data creation process of the embodiment.

FIG. 109 is a flowchart showing a subroutine of hole time series prediction bonus ball number data creation processing of the embodiment.

FIG. 110 is a flowchart showing a subroutine of a hole time series prediction premium additional ball number data creation process of the embodiment.

FIG. 111 is a flowchart showing a subroutine of hole time-series forecast exchange amount data creation processing of the embodiment.

FIG. 112 is a flowchart showing a subroutine of a hole time-series predicted amount-of-collected-balls amount data creation processing of the embodiment.

FIG. 113 is a flowchart showing a subroutine of time series prediction data creation processing of the embodiment.

FIG. 114 is a diagram illustrating a procedure of creating time series prediction data according to the embodiment.

FIG. 115 is a diagram illustrating a procedure of creating time series prediction data according to the embodiment.

FIG. 116 is a diagram illustrating a procedure of creating time series prediction data according to the embodiment.

FIG. 117 is a flowchart showing a subroutine of hall time-series forecast expected profit data creation processing of the embodiment.

FIG. 118 is a flowchart showing a subroutine of an in-business-time screen process of the same example.

FIG. 119 is a flowchart showing a subroutine of hole performance prediction screen appearance processing of the embodiment.

FIG. 120 is a flowchart showing a subroutine of hall performance prediction screen event processing of the embodiment.

FIG. 121 is a flowchart showing a subroutine of hole score prediction screen data update processing 1 of the embodiment.

FIG. 122 is a flowchart showing a subroutine of hole performance prediction screen data update processing 2 of the embodiment.

FIG. 123 is a flowchart showing a subroutine of gaming machine operation screen appearance processing in the embodiment.

FIG. 124 is a flowchart showing a subroutine of gaming table operation screen event processing of the embodiment.

FIG. 125 is a flowchart showing a subroutine of a model-specific operating screen data update process of the embodiment.

FIG. 126 is a flowchart showing a subroutine of a model-specific operation screen appearance process of the embodiment.

FIG. 127 is a flowchart showing a subroutine of interrupt event monitoring timer processing of the embodiment.

FIG. 128 is a flowchart showing a subroutine of interrupt event monitoring timer processing of the embodiment.

FIG. 129 is a flowchart showing a subroutine of model-specific operation screen event processing of the embodiment.

FIG. 130 is a flowchart showing a subroutine of interrupt event screen event processing of the embodiment.

131 is a flow chart showing a subroutine of a store closing screen process of the embodiment. FIG.

FIG. 132 is a flowchart showing a subroutine of a shop closing screen process initialization process of the embodiment.

FIG. 133 is a flowchart showing a subroutine of weather input processing of the embodiment.

FIG. 134 is a flowchart showing a subroutine of aggregating process 1 standby process of the embodiment.

FIG. 135 is a flowchart showing a subroutine of post-closing data editing processing of the embodiment.

FIG. 136 is a flowchart showing a subroutine of next business setting screen appearance processing of the embodiment.

FIG. 137 is a flowchart showing a subroutine of next business setting screen restoration processing of the embodiment.

FIG. 138 is a flowchart showing a subroutine of next business setting screen data output processing of the embodiment.

FIG. 139 is a flowchart showing a subroutine of next business setting processing of the embodiment.

FIG. 140 is a flowchart showing a subroutine of target sales amount change processing of the embodiment.

FIG. 141 is a flowchart showing a subroutine of target profit change processing of the embodiment.

FIG. 142 is a flow chart showing a subroutine of setting change processing for each unit of the embodiment.

FIG. 143 is a flowchart showing a subroutine of setting update processing 1 for each unit of the embodiment.

FIG. 144 is a flow chart showing a subroutine of the setting update processing 2 for each unit of the embodiment.

FIG. 145 is a flow chart showing a subroutine of the setting update processing 3 for each unit of the embodiment.

FIG. 146 is a flow chart showing a subroutine of the setting update processing 4 for each unit of the embodiment.

FIG. 147 is a flowchart showing a subroutine of setting UP processing of the embodiment.

FIG. 148 is a flowchart showing a subroutine of setting DOWN processing of the embodiment.

FIG. 149 is a flow chart showing a subroutine of hole performance calculation processing of the embodiment.

FIG. 150 is a flowchart showing a subroutine of aggregating process 2 standby process of the embodiment.

FIG. 151 is a diagram showing a main screen of the business analysis apparatus of the embodiment.

FIG. 152 is a diagram showing a setting screen according to the embodiment.

FIG. 153 is a view showing a hall performance information screen of the embodiment.

FIG. 154 is a diagram showing a display example of a plurality of screens according to the embodiment.

FIG. 155 is a diagram showing a display example of a plurality of screens according to the embodiment.

FIG. 156 is a diagram showing a model-specific operation screen of the embodiment.

FIG. 157 is a diagram illustrating the appearance status of the interrupt event screen according to the first embodiment.

FIG. 158 is a diagram showing an interrupt event screen in the embodiment.

FIG. 159 is a diagram showing a weather input screen according to the embodiment.

FIG. 160 is a diagram showing a next business day hall performance prediction screen of the embodiment.

FIG. 161 is a view showing a platform adjustment item selection screen of the embodiment.

FIG. 162 is a diagram showing a platform adjustment data screen of the embodiment.

FIG. 163 is a diagram showing a modified display example of platform adjustment data according to the embodiment;

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 game shop 2 card management company 11 card management device 12 management analysis device (information processing device of a game hall) 31, 31a-31n gaming machine (enclosed ball type gaming machine) 60 printer 74, 74a, 74b display unit 100 remote control device ( Remote control device) 151 workstation 152 graphic interface 153 parallel interface 154 audio interface 155 SCSI host adapter 156 ATM interface 159 video scan converter 160 display device (CRT) 162 speaker 178 RAM 187 hard disk device (HDD) 188 magneto-optical disk device (MO) ) 189 Digital tape storage device (DAT) 191 Keyboard 192 Mouse 193 CD-ROM device

Claims (7)

[Claims] 1. An information processing device of a game arcade for collecting information of a game arcade and predictively notifying management information from the collected information, and at least a predictive visitor number calculation means for predicting next visitor number information, Based on the predicted total used game value information calculation means for calculating the predicted total used game value information of the next entire game area based on the next predicted number of people visiting the store, and at least based on the predicted total used game value information of the entire next game area Based on the predicted game machine used game value information calculating means for calculating the predicted total game game value information for each next game machine and the game machine setting information and the predicted total game value information used for each game machine next time, Forecast sales / profit information computing means for computing the forecast sales information and forecast profit information, and a display for displaying the forecast sales information or forecast profit information based on the output of the forecast sales / profit information computing means An information processing device in a game hall, comprising: 2. An information processing device for a game arcade, which collects information about a game arcade and predicts and notifies management information from the collected information, and calculates the next predicted visitor traffic count from past time-series visitor traffic count information. Based on the predicted visitor number information calculating means, the predetermined past total used game value information, the predetermined past number of visitor information, and the predicted visitor number information calculated by the predicted visitor number information calculating means Predicted total used game value information calculating means for calculating the estimated total used game value information of the entire game hall, total used game value information for a predetermined past period, used game value information for each predetermined past past gaming machine, and game Use by predicted game machine for calculating next predicted used game value information for each game machine based on the installed machine number information and the predicted total used game value information calculated by the predicted total used game value information calculation means Based on the game value information calculation means, the game machine setting information, and the next predicted used game value information for each game machine calculated by the predicted game machine-specific used game value information calculation means, next predicted sales information and Any one of the forecast sales / profit information computing means for computing the forecast profit information, and the forecast sales information, the forecast profit information, or the gaming machine set value for each gaming machine based on the output of the forecast sales / profit information computing means. An information processing device in a game hall, comprising: a display unit for displaying the above information. 3. The information processing apparatus at a game arcade according to claim 1, wherein the display means displays the predicted visitor number information calculated by the predicted visitor number calculation means. 4. Predicted gaming machine operating rate information is calculated based on business hours information, predicted total used gaming value information calculated by the predicted total used gaming value calculating means, and installed machine number information. 4. A predicted gaming machine operating rate information calculating means, wherein the display means displays the predicted gaming machine operating rate information calculated by the predicted gaming machine operating rate information calculating means. An information processing device for a game hall according to any one of the above. 5. A forecast information change input unit for inputting a change of the forecast sales information or the forecast profit information calculated by the forecast sales / profit information calculating unit, and the forecast sales information changed by the forecast information change input unit or A gaming machine setting information variable calculation means for varying the gaming machine setting information associated with the gaming machine based on the predicted profit information to calculate a value approximate to the changed predicted sales information or predicted profit information. The game machine according to any one of claims 1 to 4, wherein the display means displays a set value of the game machine setting information calculated by the game machine setting information variable calculation means. Information processing equipment. 6. The gaming machine setting information information change input means for changing and inputting the gaming machine setting information for changing the gaming machine setting information associated with the gaming machine, and the predicted sales / profit information calculating means, Next based on the gaming machine setting information changed by the gaming machine setting information information change input means and the predicted used gaming value information for each gaming machine calculated by the predicted gaming machine used gaming value information calculating means 6. The information processing apparatus for a game arcade according to claim 1, further comprising: forecast sales / profit information recalculation means for recalculating the forecast sales information and the forecast profit information. 7. The information processing device in the game arcade is connected to a management device for exchanging information with a terminal device such as a game machine so that information can be transmitted, and the set game machine setting information is stored in the management device. 7. The information processing apparatus for a game arcade according to claim 1, further comprising an information transfer means for transferring the information to the game machine.