JP2019198419A - Game device and program - Google Patents

Abstract

To provide a game device comprising a function for searching a past model of a game machine which comprises a game tendency similar to that of a new model of a game machine.SOLUTION: A game device capable of acquiring information related to a plurality of models of game machines installed in a game parlor comprises: first game numerical value acquisition means capable of acquiring a first game numerical value which is a numerical value related to a first model of a game; second game numerical value acquisition means capable of acquiring a second game numerical value which is a numerical value related to a second model of a game different from the first model of a game; correlation coefficient calculation means for calculating a correlation coefficient related to a correlation between the first and second models, on the basis of the acquired first game numerical value and second game numerical value acquired in a specific period; and game tendency similarity determination means for determining that, the game tendencies of the first model and second model are similar, when the correlation coefficient calculated by the correlation coefficient calculation means is included in a standard range.SELECTED DRAWING: Figure 7

Description

  The present invention relates to a gaming apparatus capable of acquiring information related to a plurality of types of gaming machines.

In game centers where gaming machines such as slot machines and pachinko machines are installed, gaming devices such as hall computers that can receive game information output from the gaming machines are installed.
As this type of gaming apparatus, for example, Patent Document 1 discloses a gaming management apparatus that outputs an operation record for a specific model.

JP 2002-166020 A

  However, the conventional gaming device has room for improvement.

  In order to solve the above-described problems, a gaming device according to the present invention is a gaming device capable of acquiring information relating to a plurality of types of gaming machines installed in a game arcade, and is a first gaming numerical value that is a numerical value relating to a first type of gaming. A first game value acquisition means capable of acquiring a second game value acquisition means capable of acquiring a second game value that is a value related to a game of a second model different from the first model, and the acquired in a specific period Based on the first game value and the second game value, the correlation coefficient calculation means capable of calculating a correlation coefficient related to the correlation between the first model and the second model, and calculated by the correlation coefficient calculation means When the correlation coefficient is included in the reference range, the game tendency similarity determination unit can determine that the game tendency of the first model and the game tendency of the second model are similar.

1 is an overall configuration diagram of a game system. It is a systematic diagram showing the flow of information in the game system. It is explanatory drawing of the transaction information in the sand with each stand counting function. It is a block diagram which shows the internal structure of a hall computer. It is a data table which shows the transaction history of transaction information. It is a chart which shows the judgment conditions of the game period for every player. It is a chart which shows the judgment conditions for judging that the game tendency of model X and the game tendency of model Y are similar. It is a data table which shows the log | history of the number of outs of 1 week of model AE and Z. It is a table | surface which shows the mutual correlation coefficient in model AE and Z. It is a determination result when the game tendency similarity determination based on the condition 1 is performed for each model A to E and Z with brute force. It is a graph which shows the game tendency of the model determined to be similar to the game tendency of the model Z based on a correlation coefficient. It is a graph for demonstrating the tolerance | permissible_range of model AE and Z. It is a determination result when the game tendency similarity determination based on Condition 2 is performed for each model A to E and Z in a round robin manner. It is a graph which shows the game tendency of the model determined to be similar to the model Z based on the correlation coefficient and the allowable range. It is a figure which shows the example of a display of similarity.

A preferred embodiment of a gaming apparatus according to the present invention will be described with reference to FIGS.
Hereinafter, an example in which the hall computer 50 is applied as a gaming apparatus will be described.
However, in place of the hall computer 50, each unit 20 with a counting function, a gift exchange device 60, a counter, a ball server 70, a checkout machine 80, a management server for managing member information, a clerk call and game data can be displayed. Other game devices such as a call lamp and a game information display device can also be applied.
The hall computer 50 is a gaming device capable of collecting various information related to a game arcade where a plurality of gaming machines 10 are installed. As shown in FIG. 1, the gaming machine 10, the sand 20 with a counting function, A computer 30, an island computer 40, a game medium such as a game ball or a medal (hereinafter, the game medium may be expressed as “ball”) and a prize exchange device 60 for exchanging a prize and a player's possession A game system is configured together with a managed ball server 70, a settlement machine 80, and the like.

The gaming machine 10 includes a pachinko machine 10a and a slot machine 10b.
For example, in the slot machine 10b, when a player inserts a game medium such as a medal and depresses a start lever, a plurality of reels displaying a predetermined symbol start to rotate, and a plurality of stops corresponding to each reel. A game is provided in which a rotating reel is stopped by depressing a button at an arbitrary timing, and a predetermined number of game media are paid out according to the arrangement of symbols of the stopped reel.

The gaming state of the slot machine 10b includes a normal gaming state in which game media is consumed at a predetermined rate, and a special gaming state in which an increase in gaming media can be expected from the normal gaming state and is advantageous for the player.
The special game state includes a big bonus (BB), regular bonus (RB), etc. (hereinafter also referred to as “winning”), and when winning a prize after winning internally, for example, a large amount of game media of 100 or more are paid out. It is.
Such a slot machine 10b can set six stages of setting values of normal 1 to 6 having different winning probabilities.
The higher the set value, the easier it is to win, the smaller the value, the harder it is to win, etc., so that the payout rate can be adjusted according to the size of the set value.
In this way, the setting value has a direct effect on the game play rate, so it depends on the daily setting whether it is an attractive game stand for the player, and even at the amusement store, sales etc. depend on the daily setting. This is important setting information that can be influenced.
For this reason, the set value is normally set by a responsible person such as a store manager.

Sand 20 with counting function (20a is for game balls, 20b is for medals) is the number of game media acquired in the corresponding gaming machine 10, the refund (payout) of the counted game media, the input Cash and games such as lending of game media according to the amount of money, and issuance (also referred to as return or discharge) of storage media (for example, IC cards) that can specify (store) the number of counted game media and the balance of the input amount Various operations related to trading of a value medium such as a medium can be executed.
For example, the number of acquired game media is counted by inserting the game media from the insertion port provided at the lower part of the sand 20 with each vehicle counting function, and the refund of the counted game media is performed by the player. This is done by paying out the game medium from a predetermined payout outlet based on the payout operation by. Further, the rental of the game medium according to the amount of money to be inserted is performed by paying out the game medium from a predetermined payout port based on the lending operation by the player.
The gaming machine 10 and the sand with counting function 20 are each provided with a communication means, and are connected to a gaming device such as the hall computer 50 via a predetermined network (for example, a local area network) so that data communication is possible. Yes.

In a game hall equipped with such a game system, a player plays a game along the following game flow.
First, at the start of the game, the player lends the game media by putting cash into the sand 20 with each vehicle counting function and performing a predetermined lending operation. The rented game medium is inserted into the gaming machine 10 and the game is started. The game media acquired as a result of the game are put into each of the sands with a counting function 20 and counted by performing a predetermined counting operation on each of the sands with a counting function 20. When the counted game medium is used again in the game, the game medium can be paid out by performing a predetermined payout operation on each of the counter-equipped sands 20. When the game is finished, a card in which the remaining number of game media counted and the balance of the inserted cash is recorded by performing a predetermined return operation on each sand 20 with a counting function is returned.
When the returned card is handed over to the store clerk, the gift exchange device 60 performs a gift exchange process based on the operation of the store clerk or the like. In this prize exchange process, the remaining number of game media is read from a card via a card reader 60a provided in the prize exchange apparatus 60, and a settlement process with a prize corresponding to this remaining number is executed.

  In the game flow as described above, as shown in FIG. 2, the hall computer 50 receives each game information from the gaming machine 10 and receives transaction information from each sand 20 with the counting function.

The game information received from the gaming machine 10 includes “out information” including an out signal from which the number of game media inserted (out number) can be calculated, and a safe signal from which the number of game media payout (safe number) can be calculated. “Safe information”, “Status information” indicating the occurrence of a game that occurs in the gaming machine 10 and is advantageous to the player (for example, a big hit or a bonus (including AT, ART, etc.)), 1 game There is "start information" that indicates the execution of.
Such game information is transmitted to the hall computer 50 through the network computer 30 and the island computer 40 via the network together with information (such as a machine number) that can identify each gaming machine 10. The game information is sequentially stored for each gaming machine 10.

Each of the sand counters 20 with a counting function is used to count the game media acquired in the corresponding gaming machine 10, refund the counted game media, lend the game media according to the input amount, and count the games This is because it is configured to be able to issue a storage medium (hereinafter referred to as a card) that can specify the number of media (hereinafter referred to as game media, possession balls or possession balls) and the balance of the input amount. The transaction information corresponding to each operation is stored.
The transaction information includes, for example, “Bill insertion”, “Card insertion”, “Card return”, “Lending”, “Count”, “Refund”, “Card stack”, “Card set” as shown in FIG. and so on.

(A) “Bill insertion” is information indicating the insertion of a banknote by a player, and the insertion of the banknote, the denomination and the like are specified from this information.
(B) “Card insertion” is information indicating insertion of a card by a player, and from this information, a card that can identify the insertion of the card, the balance of the inserted amount, the remaining number of possessions, and the inserted card ID etc. are specified.
(C) “Card return” is information indicating a card return operation by the player, and from this information, it is possible to identify the return of the card, the balance of the inserted amount, the remaining number of balls, and the returned card. A card ID or the like is specified.
(D) “Lending” is information indicating a lending operation by the player, and from this information, a lending amount (number of lending balls), a balance, and the like are specified.
(E) “Counting” is information indicating a counting operation by the player, and the number of balls counted, the remaining number of balls, and the like are specified from this information.
(F) “Refund” is information indicating a payout operation by the player, and the number of balls repaid from the possession balls, the remaining number of possessions, and the like are specified from this information.
(G) “Card stack” is information indicating the card transport from the card reader / writer to the card storage unit provided in the sand 20 with each unit counting function. From this information, the stack of cards, the balance of the input amount, The remaining number of possession balls, the card ID that can identify the stacked cards, and the like are specified.
(H) “Card set” is information indicating the card transport from the card storage unit to the card reader / writer. From this information, the card is set, the balance of the inserted amount, the remaining number of possessions, and the set A card ID or the like that can identify the card is specified.
In this embodiment, each sand 20 with counting function is configured to have a card writer, and information such as the balance of the input amount, the remaining number of possessions, and the card ID can be directly written to the card. In addition, or instead of this, information such as the balance of the amount of money to be inserted, the number of remaining balls, etc. is associated with the card ID and each sand 20 with a counting function and other gaming devices (for example, the hall computer 50 and the holding server 70) ) May be stored and managed.
In addition, although “card insertion” and “card set” are described separately, “card set” may be included in “card insertion”.
In addition, when counting the number of acquired game media with a counter installed at the island edge or the like, sand without a function of counting each vehicle may be used. In this case, in the counter, information indicating which game machine the game medium to be counted is acquired is registered.

The transaction history of such transaction information (sometimes simply referred to as transaction information or transaction history, the same applies hereinafter) corresponds to the time (time) when the transaction occurred in the storage means such as the memory provided in the sand 20 with each counter. In addition, the information is sequentially stored and divided into predetermined periods such as every predetermined business day (for example, one business day).
The transaction history of the stored transaction information is stored in response to a request from the ball server 70 or the hall computer 50 that manages the player's ball for each occurrence of the transaction or for each divided period. The attached sand 20 is transmitted to the holding ball server 70 together with information capable of specifying it, and stored in a storage means such as a memory provided in the holding ball server 70. Further, in response to a request from the hall computer 50, it is transmitted from the holding server 70 to the hall computer 50 at once, and is stored as information for each gaming machine 10 together with the gaming information (see FIG. 2). The transmission timing does not have to be a batch, and can be set to an arbitrary timing.

As shown in FIG. 4, the hall computer 50 includes an input unit 51 including input means such as a keyboard and a mouse, a communication unit 52 that performs data communication with the base computer 30, the island computer 40, and the like, and a storage including storage means such as a hard disk. The information processing device includes a unit 53, a display unit 54 having a display unit such as a liquid crystal display device, a control unit 55 (computer) that controls each unit, and the like, and is configured as an information processing device operated by a store clerk or the like in a game hall.
Such a hall computer 50 performs various operations based on a program stored in the storage unit 53.
For example, in the hall computer 50, based on game information and transaction information input via the communication unit 52, the following game information can be aggregated and calculated.
For example, the number of outs from “out information” and the number of safes from “safe information” are totaled. Also, a difference number (also referred to as a difference number) indicating a difference between the out number and the safe number is calculated. Further, as will be described later, the investment amount can be calculated from the history of “loan” included in the transaction information.
The hall computer 50 stores the game data thus tabulated and calculated in the storage unit 53 for each gaming machine 10 and every business day (for example, in units of one day).
Such game data is aggregated and calculated not only for each gaming machine 10 but also for each group such as each machine, each model, each rental rate, and each game hall (store). Can be stored for each.
Further, the game data is stored not only for every business day but also for each different unit of business period such as a plurality of business days (for example, one week, one month).
In the hall computer 50, the store clerk can operate the input unit 51 to input a set value set in each gaming machine 10, so that the input set value is stored in the base of the gaming machine 10. The number, model, and business day are associated with each other and stored in the storage unit 53.
As a result, setting values set in the past can be extracted and referenced by designating the gaming machine, model, business day, period, and the like.

Furthermore, the hall computer 50 specifies one game period in the gaming machine 10 by the control unit 55 functioning as a game period specifying means.
Specifically, the player determines the game period, which is the period from the start of the game of one player to the end of the game, by determining the replacement of the player based on the transaction information received from the sand 20 with each unit counting function. Identify every time.
An operation for specifying such a game period will be described with reference to a transaction history of transaction information shown in FIG.

FIG. 5 exemplifies a transaction history (a time period from “15:19” to “16:19”) in one sand 20 with each vehicle counting function. The order of the transaction information shown in FIG. 5 is arranged so that the transaction time is from early transaction time to late transaction time from the top to the bottom.
In addition, there are two types of cards: a member card that is lent or transferred in advance from a game hall to a player who is registered as a member, and a general card that can be used by a general player who does not have a member registration (so-called visitor card) This transaction history shows a transaction history using a general card. Moreover, although not shown in particular, in this transaction information, a card classification capable of specifying the type of card used for the transaction can be provided.
From such a transaction history, the control unit 55 specifies a game period for each player.
The game period is specified based on the determination conditions shown in FIGS. 6 (a) and 6 (b).
FIG. 6A shows the determination conditions for determining the replacement of the player, and FIG. 6B shows the determination conditions for determining the continuous game of the player.

Specifically, the condition “a” is “card insertion” indicating that there is no balance and no remaining number of players, and the replacement of the card is assumed from such “card insertion”. Therefore, it is determined that the player has been changed before and after the “card insertion” due to the establishment of such a condition.
For example, in the example shown in FIG. 5, in transaction number 4 (time “15:25”), there is “no card balance” indicating no balance (¥ 0) and no remaining ball (0 balls). It is determined that the player has been changed later.

Further, the condition b is a player replacement condition that a card with an ID different from the returned card is inserted. Whether or not this condition is successful is determined from “card return” and subsequent “card insertion” in the transaction information. In particular, it is determined that the condition is satisfied when the card IDs specified from “card return” and “card insertion” are different. In addition, in “card insertion”, the condition is satisfied that at least one of the balance and the remaining number of coins to be specified indicates “Yes”.
With such a combination of transaction information, it is considered that the player has been replaced during each transaction. In this case, for example, the game period of the previous player can be regarded as “card return”, and the game period of the subsequent player can be regarded as “card insertion”.

For example, in the example shown in FIG. 5, the card ID (003) specified from the “card return” in the transaction number 17 (time “15:48”), and the transaction number 18 (time “15:50”) following the card ID. Since the card ID (004) specified from “card insertion” indicating that there is a balance (¥ 500) is different from each other, the game period of the previous player is until “card return”, and after “card insertion” It can be regarded as the game period of the player.
In addition, when each card ID specified from "card return" and "card insertion" which shows that there is a balance or a remaining number of balls following this is the same, for example, in the example shown in FIG. Card ID (003) specified from “card return” in “15:45”) and card ID (003) specified from “card insertion” in transaction number 15 (time “15:46”) following this Are the same, it can be determined that the condition f shown in FIG. 6B is satisfied, and it can be determined that the game is continued by the same player.

The condition c is a condition that the card insertion after the card stack is a player replacement condition. The success / failure of this condition is determined from “card stack” followed by “card insertion” in the transaction information. In particular, it is determined that the condition is satisfied when at least one of the balance specified from “card insertion” and the remaining number of possessed balls indicates “present”.
With such a combination of transaction information, the end of the game is specified from the “card stack”, and the start of a new game is specified from “card insertion” indicating that there is a balance or the remaining number of possessions, It can be determined that the player has been replaced. In this case, for example, the game period up to the “card stack” can be regarded as the game period of the previous player, and the game period of the subsequent player can be regarded as after the “card insertion”.

  For example, in the example shown in FIG. 5, there is a “card stack” at transaction number 24 (time “15:54”), followed by a balance (¥ 2000) and a balance at transaction number 25 (time “16:00”). From “card insertion” indicating the number of balls remaining (125 balls) to “card stack” can be regarded as the game period of the previous player, and from “card insertion” as the game period of the subsequent player.

The condition d is a condition that a player inserts a bill after a predetermined time (for example, 5 minutes) has elapsed after the cards are stacked. Whether or not this condition is successful is determined from “card stack” followed by “insert bill” in the transaction information. In particular, it is determined that the condition is satisfied when the time from “card stack” to “banknote insertion” exceeds a predetermined time.
With such a combination of transaction information, the end of the game is specified from the “card stack”, and the start of a new game is specified from the “insert banknote” after a predetermined time has elapsed. Can be determined. In this case, for example, the game period of the previous player can be regarded as “card stack”, and the game period of the subsequent player can be regarded as “banknote insertion”. Further, the predetermined time can be set to a time that can be appropriately set by a game hall manager or the like, for example, “5 minutes”.
For example, in the example shown in FIG. 5, the “card stack” at transaction number 31 (time “16:06”) and the transaction number 32 (time “16:13”) after 7 minutes have elapsed from this “card stack”. From “Bill insertion” to “Card stack” can be regarded as the game period of the previous player, and from “Bill insertion” can be regarded as the game period of the subsequent player.
When the “card stack” and the subsequent “banknote insertion” are stored within a predetermined time (for example, 5 minutes), it is determined that the condition g shown in FIG. 6B is satisfied, and is continued by the same player. It can be regarded as a game.
For example, in the example shown in FIG. 5, the “card stack” at the transaction number 36 (time “16:17”) and the transaction number 37 (time “16” after two minutes have passed since this “card stack”). : 19 ”), the continuous game by the same player is determined.

The condition e is a condition for continuing the game by the same player with the counting operation after card return or card stacking. The success / failure of this condition is determined from “card return” or “card stack” indicating that there is a balance, and “count” following this.
By such a combination of transaction information, for example, from “card return” indicating that there is a balance, a return operation based on the player's judgment that the need for lending has been eliminated due to occurrence of hit is assumed, From the “stack”, it is assumed that the game is about to end. From the “count”, a count operation of the acquired game media based on the occurrence of winning is assumed.
A combination of such a series of transaction information can be determined as a continuous game by the same player.
In this case, there is no “card insertion” or “card insertion” indicating that there is a balance or the like between “card return” or “card stack” and “count”.

For example, in the example shown in FIG. 5, “card return” indicating that there is a balance (¥ 500) in transaction number 9 (time “15:35”) and subsequent transaction number 10 (time “15:36”) Based on the “count”, a continuous game by the same player is determined.
Further, from the “card stack” at the transaction number 20 (time “15:51”) and the “count” at the subsequent transaction number 21 (time “15:53”), the continuous game by the same player is determined. Is done.

In the example shown in FIG. 5, at least six game periods surrounded by thick lines are specified by specifying the game periods performed based on the conditions shown in FIGS. 6A and 6B as described above. (Transaction numbers 1-5, 6-17, 18-24, 25-28, 29-31, 32-38).
By specifying such a game period, it is possible to estimate the number of players who have played a game in the gaming machine 10 provided in the sand 20 with each vehicle counting function. In this case, “15:19” to “16 : 19 ”, it can be estimated that six players played the game.

Thus, the hall computer 50 can specify the game period for each player based on the transaction information.
Since the hall computer 50 can specify the game period for each player in this way, for example, the investment amount in the game period is totaled based on transaction information (the number of loans) in the game period, Based on the game information (out number), the number of game media used in the game period can be totaled, or the difference number in the game period can be calculated based on the out number and the safe number in the game period.
In the hall computer 50, numerical information related to the game can be acquired for each model.
For example, the total number of outs (first game value) in model X (first model) is totaled (first game value acquisition means), or the total number of outs in model Y (second model) is totaled (second game value acquisition) Means).
Also, the “out average per person for model X” and “out average per person for model Y” obtained by dividing the total number of outs for model X and model Y by the number of players of model X and model Y, respectively, It can also be tabulated as a game value and a second game value.
Note that model X and model Y indicate any two models having different models.

The hall computer 50 of the present embodiment can determine whether or not the game trends of these models are similar (similar) based on the game values of the two different models acquired in this way. .
FIG. 7 is a chart showing determination conditions for determining that the game tendency of the model X and the game tendency of the model Y are similar.
That is, as shown in FIG. 7, a game tendency similarity determination process can be performed based on the conditions 1 and 2.

[Condition 1]
Condition 1 is that the correlation coefficient between the number of outs of model X and the number of outs of model Y in a specific period is included in the reference range, and when this condition is satisfied, the gaming tendency of model X and model Y Are determined to have similar game tendencies (see FIG. 7).
The control unit 55 performs a process of calculating a correlation coefficient related to the correlation between the model X and the model Y based on the number of outs of the model X and the number of outs of the model Y acquired as a correlation coefficient calculation unit. .
The “out number of model” can be the total number of outs of the model or the average out value per person of the model. In this embodiment, the average out value per person of the model is used. Is simply described as “model out number”.

The correlation coefficient is known as an index indicating the relationship between two types of data, and generally has a strong correlation when included in the range of “0.7 to 1” or “−0.7 to −1”. It is said that there is.
Such correlation coefficients are used to find, for example, the correlation between mathematics and science grades, the correlation between age and annual income, the correlation between the height of the parent and the child, the correlation between study time and academic ability, etc. Although it was used, it was not used to determine whether the gaming tendency of gaming machines is similar.

The correlation coefficient can be calculated using the following equation.

A specific method of calculating the correlation coefficient in the present embodiment will be described with reference to FIG.
FIG. 8 is a history of the number of outs for the models A to E and Z. The number of outs per business day in seven days (corresponding to a specific period) after the gaming machines of each model are installed (introduced) in the amusement hall. Is illustrated.
In this embodiment, the models A to E have passed a considerable number of days (for example, several months or more) after introduction, and a slot machine that stores (accumulates) various information (out number, sales, gross profit, etc.). 10b (“past model”) is assumed, and the model Z is assumed to be a slot machine 10b (“new model”) in which only 7 days have passed since introduction.

A method for calculating the correlation coefficient between the model B and the model D will be described.
Specifically, a method for calculating the correlation coefficient based on the respective number of outs in this period, with 7 days after the model B and the model D are introduced into the game hall as the specific period, will be described.
However, the specific period is not limited to the period after introduction, and is not limited to seven days.
Further, any game numerical value may be used as long as it is numerical information (game numerical value) related to a game, such as a safe number and a difference number.
The correlation coefficient can be calculated by substituting variables corresponding to the above formula.
Specifically, the calculation of the correlation coefficient by the above formula is performed as shown in the following (1) to (6): “average”, “deviation”, “variance”, “standard deviation”, “covariance” This is equivalent to calculating the “correlation coefficient” through

(1) “Average”: Total number of outs / days elapsed “Average of number of outs of model B”; (1798 + 1332 + 1217 + 9296 + 2062 + 2519 + 2441) ÷ 7 = 2952
“Average of the number of outs of model D”; (2688 + 2842 + 4701 + 11630 + 2192 + 1026 + 0) ÷ 7 = 3583

(2) “Deviation”: Number of outs per business day−Average “Each deviation of model B”; “−1154” (= 1798-2952), “−1620” (= 1332-2952), “−1735” ( = 1217-2952), “6344” (= 9296-2952), “−890” (= 2062-2952), “−433” (= 2519-2952), “−511” (= 2441-2952)
"Each deviation of model D";"-894" (= 2689-3583), "-741" (= 2842-3583), "1118" (= 4701-3583), "8047" (= 11630-3583), "-1391" (= 2192-3583), "2557" (= 1026-3583), "-3583" (= 0-3583)

(3) “Dispersion”: Total of square of deviation / elapsed days “Dispersion of model B”; ((−1154) ² + (− 1620) ² + (− 1735) ² + (6344) ² + (− 890) ² + (433) ² + (− 511) ² ) ÷ 7 = 6921912
“Dispersion of model D”; ((−894) ² + (− 741) ² + (− 1118) ² + (8047) ² + (− 1391) ² + (2557) ² + (− 3583) ² ) ÷ 7 = 12666210

(4) “standard deviation”: square root of variance “standard deviation of model B”; 2631
“Standard deviation of model D”; 3559
(5) “Covariance”: Average of product B and model D deviations for each business day “Model B covariance”; ((1798-29552) × (2689-3583) + (1332-2952) ) × (2842-3583) + (1217-2952) × (4701-3583) + (9296-2952) × (11630-3583) + (2062-2952) × (2192-3583) + (2519-2952) × (1026-3583) + (2441-2952) × (0-3583)) ÷ 7 = 79331

(6) “Correlation coefficient”: covariance / (standard deviation of model B × standard deviation of model D)
“Correlation coefficient between model B and model D” = 793131 ÷ (2631 × 3559) = 0.8470
Thereby, the correlation coefficient between the model B and the model D is calculated as “0.8470”.
Correlation coefficients between models B and models other than model D (models A, C, E, and Z) can be calculated in the same manner.
For models other than model B (models A, C, D, E, and Z), correlation coefficients with other models (models A to E and Z) can be calculated in the same manner.
As a result, as shown in FIG. 9, for each model A to E, Z, correlation coefficients with other models can be calculated.

When the calculated correlation coefficient is included in the reference range, the control unit 55 determines that the game tendency of the model X and the game trend of the model Y are similar, and the correlation coefficient is the reference range. If the game tendency is not included in the model X, the game tendency of the model X and the game trend of the model Y are determined to be not similar.
The reference range of this embodiment is “0.9 to 1”.
That is, when the correlation coefficient between the model X and the model Y is included in the range of “0.9 to 1”, it is determined that the game tendency of the model X and the game tendency of the model Y are similar.
In general, when the correlation coefficient is determined to have strong correlation when included in the range of “0.7 to 1”, the correlation coefficient is “0.9 to 1” as in the present embodiment. When it is included in the range, it is determined that the game tendency is similar. As a result of verifying a plurality of correlation coefficients between models that are known to have similar game trends, the correlation coefficient is “0.9. In many cases, the correlation coefficient is less than "0.9" as a result of verifying the correlation coefficient between models that do not have similar game trends. is there.
The reference range can be set to an arbitrary range other than “0.9 to 1”.
The “reference range” is a concept including a “reference value”, and an arbitrary reference value can be set as the reference range.
For example, a predetermined reference value can be set. In this case, when the correlation coefficient matches this reference value (including a case where they substantially match), it can be determined that the game tendency is similar.
In addition, when the lower limit is set as the reference value, it is considered that the reference value is greater than or equal to the reference value, and when the upper limit is set as the reference value, the reference value is equal to or less than the reference value or less than the reference value. Can be considered.

FIG. 10 shows a determination result when the game tendency similarity determination based on the condition 1 is performed for each model A to E and Z in a round robin manner. “OK” is similar and “NG” is not similar.
The hall computer 50 can display such a determination result on the display unit 54.
For this reason, the manager of the game hall can easily grasp which models have similar game trends (not similar).
For example, according to FIG. 10, it can be understood that model B and model D, model D and model E are not similar in game tendency, and other models are similar to each other.
In addition, by specifying an arbitrary model (also referred to as a search model) and performing a similar search operation, it is possible to detect a model (also referred to as a similar model) determined to have a similar game tendency to the search model.
For example, by performing the similarity search operation by specifying the model Z as the search model, the models A to E can be detected and displayed as the similar models.
In this way, for example, the models A to E can be specified as the past models having a game tendency similar to the new model Z.
For this reason, the past information of the past models A to E can be referred to or reflected in the future operation of the new model Z.
For example, among the models A to E, the setting value (for example, setting value information after the 8th day after introduction) of a model (for example, a model B with good gross profit) that changes with a preferable gaming tendency is reflected in the new model. Therefore, it can be expected that the new model will also shift to a favorable game trend.

In addition, the game tendency of similar models can be displayed in a graph.
The control unit 55 can output a graph indicating the game tendency of at least one of the model X and the model Y when it is determined by the game tendency similarity determination unit as the graph output unit.
For example, FIG. 11 is a graph showing the game tendency of similar models (models A to E) when the model Z is the search model and the similarity determination of the game tendency is performed based on the condition 1.
Specifically, FIG. 11 is a line graph with the elapsed days as the horizontal axis and the number of outs as the vertical axis, and the number of outs and the increase / decrease (game tendency) for each business day of the model Z and models A to E. It is a graph that can be seen.
The hall computer 50 can display such a graph on the display unit 54.
For this reason, the game hall manager must predict the future game trend of the new model Z based on the game trends (such as increase / decrease in the number of outs, timing of increase / decrease) of the past models A to E, which are similar models. Can do.
In addition, FIG. 11 adds not only the graph of the game tendency of the similar model but also the graph of the game trend of the search model (model Z), so the graph of the search model and the graph of the similar model can be easily compared visually. be able to.
For example, according to FIG. 11, the model B and model D graphs are similar to the model Z graph, so the game trends of model B and model D and the game trends of model Z are similar. This can also be confirmed visually.
In addition, it can be visually confirmed that there is a day (elapsed date: the fourth day) in which the number of outs is significantly different from the model Z for the model A and the model C.
In this case, the administrator can exclude the model A and the model C from the similar models and determine that the game tendency is not similar to the model Z.
Thereby, although there is a part left to a part of manager's judgment, the precision of similarity judgment can be raised.

[Condition 2]
Condition 2 is different from Condition 1 in that it is a condition used when automatically performing high-precision similarity determination.
In condition 2, in addition to condition 1, the maximum value of the number of outs of model Y in the specific period is included in the first range (maximum allowable range) based on the maximum value of the number of outs of model X in the specific period, In addition, when the minimum value of the number of outs of the model Y in the specific period is included in the second range (minimum value allowable range) based on the minimum value of the number of outs of the model X in the specific period, the gaming tendency of the model X And the game tendency of the model Y is determined to be similar (see FIG. 7).
In this case, the control unit 55 is a case where the correlation coefficient is included in the reference range as the game tendency similarity determination unit, and the maximum value of the number of models Y in the specific period is the number of models X out in the specific period. The minimum value of the model Y out number in the specific period is included in the second range based on the minimum value of the model X out in the specific period. In this case, it is determined that the game tendency of the model X and the game trend of the model Y are similar. Otherwise, the process of determining that the game trend of the model X and the game trend of the model Y are not similar is performed.

This will be described with reference to FIGS.
A method of calculating the maximum value allowable range and the minimum value allowable range will be described with reference to FIG.
As shown in FIG. 12, the “maximum value allowable range” is a range specified by the maximum value (upper limit) and the maximum value (lower limit), and the “minimum value allowable range” is the minimum value (upper limit) and the minimum value. It is a range specified by (lower limit), and can be calculated as (i) to (iv) below.
(I) Maximum value (upper limit) = maximum value + out speed × 180
(Ii) Maximum value (lower limit) = maximum value−out speed × 180
(Iii) Minimum value (upper limit) = minimum value + out speed × 180
(Iv) Minimum value (lower limit) = Minimum value−Out speed × 180
Since the “out speed” is the number of outs per unit time set for each model, it can be set to an arbitrary value.
In the present embodiment, the “out speed” of the models A to E, Z is exemplified as a case where each is set to “30 / min” (see FIG. 12).
The out-speed of the pachinko machine 10b is generally higher (faster) than the out-speed of these slot machines 10b, and can be set to “99 / min”, for example.
Note that a gaming machine with a low (slow) out speed progresses at a slower pace than a gaming machine with a high (fast) out speed.
For this reason, for example, for a model with many effects, the operation is performed so that the effects can be easily seen even during the game by setting the out speed low.
“Outspeed” is adopted as the similarity determination condition of game tendency because “number of outs” is common game information as an index indicating the degree of operation of the pachinko machine 10a and the slot machine 10b. This is because analysis can be performed.
That is, as a result of comparing and verifying the number of outs in a predetermined period for the model X and the model Y having similar game trends, the maximum value of the model Y falls within the range of “maximum value ± out speed × 180” of the model X, In addition, there are many cases where the minimum value of model Y falls within the range of “minimum value ± out speed × 180” of model X. On the contrary, the result of the same verification for model X and model Y that do not have similar game trends The maximum value of model Y does not fall within the range of “maximum value ± out speed × 180” of model X, or the minimum value of model Y falls within the range of “minimum value ± out speed × 180” of model X. This is because there are many cases where both of them are applicable, and such a case appears as a common tendency in the pachinko machine 10a and the slot machine 10b.

FIG. 13 shows a determination result when the game tendency similarity determination based on the condition 2 is performed for each model A to E and Z in a round robin manner. “OK” is similar and “NG” is not similar.
As shown in FIG. 13, there are cases where it is determined that the game tendency is not similar under condition 2 even if it is determined that the game tendency is similar under condition 1 (see FIG. 10).
For example, in the relationship with the model Z, in the case of the condition 1, it is determined that the game tendency is similar to the models A to E (see FIG. 10), but in the case of the condition 2, the game tendency is the model A, C, E. It is determined that they are not similar.
Such a determination method will be described with reference to the graph of FIG.
FIG. 14A shows a graph indicating the game tendency of a similar model when the similarity determination of the game tendency is performed based on the condition 1 with the model Z as a search model, and “maximum value of the model Z” as a reference. It is the figure which represented the "maximum value tolerance | permissible range" and the "minimum value tolerance | permissible_range" on the basis of "the minimum value of the model Z" so that visual recognition was possible.
FIG. 14B is a graph showing the game tendency of similar models (models B and D) when the similarity determination of the game tendency is performed based on the condition 2 with the model Z as the search model.
As shown in FIG. 14A, the number of outs of models A to E is the maximum value on the fourth day of the elapsed date, and the maximum value of model A and model C (about 30000) is that of model Z. Since it is not included in the maximum value allowable range (2355-13155), it is far from the maximum value of the model Z.
Further, the minimum value (5500) of the model E is not included in the minimum value allowable range (−5400 to 5400) of the model Z, and thus is far from the minimum value of the model Z.
Condition 2 determines that the models A, C, and E are not similar to the model Z and the models B and D are determined to be similar to the model Z for such reasons.
That is, even if it is determined that the model is similar based on the correlation coefficient, if the number of outs is too far to be included in the allowable range, the determination is made by excluding it from the similar model.
For example, as shown in FIG. 14B, in the relationship with the model Z, the models B and D in which the graph forms (the tendency of increase / decrease in the number of outs) are similar and the number of outs are not far apart are shown. It can be specified as a similar model.
That is, according to Condition 2, it is possible to automatically perform high-precision similarity determination.

Instead of the correlation coefficient, the “decision coefficient” can be used to determine the similarity of the game tendency.
The “determination coefficient” is a value calculated by squaring the correlation coefficient.
For this reason, when the determination coefficients of the model X and the model Y are included in the range of “0.81 (= 0.9 ² ) to 1 (= 1 ² )”, it is determined that the game trends of the model X and the model Y are similar. can do.
The “determination coefficient” can also be used as an index (similarity) indicating the degree of similarity.
For example, when the determination coefficient of model X and model Y is “0.81”, “the similarity between model X and model Y is 81%” can be displayed on display unit 54.
Further, as shown in FIGS. 15A and 15B, the similarity between corresponding models can be displayed in a pop-up manner by placing the cursor in the chart of FIG. 10 or the graph of FIG.
Thereby, the administrator can also determine whether the game tendency is similar by looking at the similarity.
The reason why the “correlation coefficient” is not used is that the correlation coefficient is a measure of a linear relationship and is inappropriate.
That is, when the correlation coefficient is used as it is as a similarity, for example, even when the correlation coefficient is “0.8” that is not included in the reference range, “similarity = 80%”, which is not similar. This is because a high degree of similarity is exhibited and matching is not achieved.
On the other hand, when the “determination coefficient” is “0.81” or more, it is determined that the game tendency is similar, and is consistent with a high similarity of “81% or more”.
For this reason, the determination coefficient can be used as an index indicating the degree of similarity.

As described above, according to the hall computer 50 of the present embodiment, the game numerical values of the two models are used, and it is determined using the correlation coefficient whether the game trends of these models are similar. ing.
Thereby, for example, it is possible to search for a past model having a game tendency similar to that of the new model.
By doing so, for example, a game trend of a past model similar to the new model can be output as a graph or data, and can be utilized for management of a game arcade such as prediction of future operation transition of the new model.
In addition, in the determination using the correlation coefficient, it is possible to search for past models that are more similar to the new model by providing an allowance range of game values, and to improve the prediction accuracy of future operation transitions in the new model Can do.

On the other hand, there is no conventional gaming device that determines whether or not the models are similar using the correlation coefficient as in the present invention, or that determines whether an allowable range is provided.
For example, the gaming management device disclosed in Japanese Patent Application Laid-Open No. 2002-166020 outputs an operation result for a specific model, but cannot predict a future operation transition in a new model.
According to the gaming apparatus of the present embodiment, it is possible to search for a past model that is more similar to the new model in the determination using the correlation coefficient, etc., and accurately predict future operation transitions in the new model. It is possible to solve all or part of such problems that the conventional gaming apparatus should improve.

The preferred embodiment of the gaming device of the present invention has been described above, but the gaming device according to the present invention is not limited to the above-described embodiment, and various modifications can be made within the scope of the present invention. Needless to say.
For example, in the above-described embodiment, an example in which the transaction information in each of the sand counters with a counting function 20 is output to the hall computer 50 via another gaming device such as the base computer 30 or the island computer 40 has been shown. You may output to the computer 50.
The game machine 10 may be a so-called enclosed game machine that uses a data-type game medium without using a real game ball or medal.

In addition, the similarity determination of the game tendency is sufficient if the game information (game value) of each model can be acquired. For example, the game information collected and totaled by the hall computer 50 is transmitted to the outside of the game hall via the communication means or the recording medium. It is also possible to input to a certain computer and perform game tendency similarity determination and graph display on an external computer.
The graph may be output for both the search model and the similar model, or only the similar model or the search model may be output.

10 gaming machines (10a pachinko machines, 10b slot machines)
20 Sand each with counting function 30 computers 40 Island computers 50 Hall computers (game machines)
53 Storage Unit 54 Display Unit 55 Control Unit

Claims (5)

In a gaming device that can obtain information on multiple types of gaming machines installed in a game hall,
A first game value acquisition means capable of acquiring a first game value that is a value related to a game of the first model;
Second game value acquisition means capable of acquiring a second game value that is a value related to a game of a second model different from the first model;
Correlation coefficient calculating means capable of calculating a correlation coefficient related to the correlation between the first model and the second model based on the first game value and the second game value acquired during a specific period;
When the correlation coefficient calculated by the correlation coefficient calculating means is included in a reference range, a game tendency similarity determining means capable of determining that the gaming tendency of the first model and the gaming tendency of the second model are similar; A gaming device characterized by comprising: The game tendency similarity determining means includes:
In the case where the correlation coefficient is included in the reference range, the maximum value of the second game value in the specific period is a first range based on the maximum value of the first game value in the specific period. If the minimum value of the second game value in the specific period is included in the second range based on the minimum value of the first game value in the specific period, the game tendency of the first model The game device according to claim 1, wherein it can be determined that the game tendency of the second model is similar. The first game value is
The number of outs in the first model,
The second game value is
The gaming device according to claim 1, wherein the number of outs in the second model. And a graph output unit capable of outputting a graph indicating a game tendency of at least one of the first model and the second model when the game tendency similarity determination unit determines that the game model is similar. The gaming device according to any one of claims 1 to 3. A computer that constitutes a gaming device capable of acquiring information on a plurality of types of gaming machines installed in a game hall,
A first game value acquisition means capable of acquiring a first game value which is a value related to a game of the first model;
Second game value acquisition means capable of acquiring a second game value that is a value related to a game of a second model different from the first model;
Correlation coefficient calculating means capable of calculating a correlation coefficient related to the correlation between the first model and the second model based on the first game value and the second game value acquired during a specific period;
When the correlation coefficient calculated by the correlation coefficient calculating means is included in a reference range, a game tendency similarity determining means capable of determining that the game tendency of the first model and the game tendency of the second model are similar. A program characterized by functioning.