JP7301341B2 - Racehorse potential ability prediction program, racehorse potential ability prediction method, racehorse potential ability prediction system, stallion candidate presentation program, stallion candidate presentation method, and stallion candidate presentation system , and a program for creating a predicted lifetime winning prize database used for these - Google Patents

Description

The present invention provides a racehorse potential prediction program, a racehorse potential prediction method, a racehorse potential prediction system, a stallion candidate presentation program, a stallion candidate presentation method, and a breed The present invention relates to a stallion candidate presentation system, and a predictive lifetime winning prize money database creation program used in these systems.

Horse racing is a bet where spectators are asked to predict the order of finish by running a racehorse a predetermined distance, and if the prediction is correct, a predetermined dividend is paid to the spectator.Including industries related to the production of racehorses. In Japan alone, the scale is about 3 trillion yen.

It is said that the latent ability of a racehorse depends greatly on its parents, that is, it has a large genetic component. Attempts have therefore been made to measure its potential by conducting genetic tests.

Ireland's Equinom (currently Plasbital), which was established in 2010 for the first time in the world, is a company that undertakes such genetic testing. As of the filing date of this patent application, this company provides a service for genetic testing of racehorse aptitude for competitive distances, and supports trainers and horse owners in deciding which races the racehorse will run.

As can be seen from the above description, it is an important factor for trainers to select races in which the racehorses can maximize their competitiveness.

Regarding the above point of view, as a known technology related to genetic testing, for example, Patent Document 1 below discloses whether a racehorse is a short-distance type, a medium-distance type, or a long-distance type by performing genetic testing. A method for determining is disclosed.

Patent No. 5667057

However, the technique described in Patent Literature 1 merely determines the aptitude type of a racehorse, and there is still a problem in evaluating the potential ability of the racehorse.

By the way, at present, in the production of racehorses, traditionally, breeders or owners with specialized knowledge take into consideration the competitive performance, pedigree, physique, personality, etc. A stallion to be mated with a broodmare is decided based on performance, pedigree, character, mating amount, or the competitive performance of horses of similar pedigree.

In other words, for racehorses that are traded for tens of millions to hundreds of millions of yen, methods to assess potential competitiveness, or selection of stallions to be mated with broodmares in order to produce racehorses with high potential competitiveness. Although this method is supported by the experience and knowledge of the producers, there are still problems with quantitative and objective judgments.

Therefore, in view of the above problems, the present invention provides a racehorse potential ability prediction program and a racehorse potential ability prediction method that can predict information for quantifying and maximizing the potential competitive ability of a racehorse. , and a racehorse potential prediction system, and a program for creating a predicted lifetime winning prize money database used in these systems.

In addition, the present invention relates to the above object, furthermore, focuses on the relationship between a broodmare and a stallion, and applies the above to present a stallion candidate for presenting an optimal stallion to a broodmare. Another object of the present invention is to provide a program, a method for presenting stallion candidates, a system for presenting stallion candidates, and a predicted lifetime win prize money database creation program used for these.

A racehorse potential competitive ability prediction program according to one aspect of the present invention for solving the above problems includes a procedure for inputting racehorse data into a computer, and predicted lifetime winning prize money data based on the input racehorse data. It is for executing the procedure of acquiring and displaying prediction information data.

In addition, a racehorse potential competitive ability prediction method according to another aspect of the present invention is a procedure for inputting racehorse data, based on the input racehorse data, predictive information data including predicted lifetime prize money data It has a procedure for obtaining and displaying.

In addition, a racehorse potential competitive ability prediction system according to another aspect of the present invention is a procedure for inputting racehorse data, based on the input racehorse data, predictive information data including predicted lifetime winning prize money data A computer recording a racehorse potential competitiveness prediction program for executing the acquisition and display procedure, a plurality of past racehorse data, and broodmare data and stallions corresponding to the past racehorse data Predicted lifetime for executing a procedure for performing machine learning including data and lifetime prize money performance data, and creating and recording prediction information data including predicted lifetime prize money data for each racehorse data and a computer in which a winning prize database creation program is recorded.

In addition, a stallion candidate presentation program according to another aspect of the present invention is a procedure for inputting broodmare data into a computer, and based on the inputted broodmare data, acquires prediction information data including predicted lifetime winning prize money data. It is for executing the procedure to be displayed by

In addition, a stallion candidate presentation method according to another aspect of the present invention includes a procedure for inputting broodmare data, and obtaining prediction report data including predicted lifetime prize money data based on the input broodmare data. and a procedure for displaying.

In addition, a stallion candidate presentation system according to another aspect of the present invention includes a procedure for inputting broodmare data, and based on the input broodmare data, acquires and displays prediction information data including predicted lifetime winning prize money data. A computer in which a program for presenting stallion candidates for executing the procedure to perform the above is recorded, a plurality of past racehorse data, broodmare data corresponding to the past racehorse data, stallion data, and lifetime winnings A predicted lifetime winning prize money database creation program for executing a procedure for performing machine learning by including data and creating and recording predicted information data including predicted lifetime winning prize money data for each racehorse data is recorded. and a computer.

In addition, a predicted lifetime winning prize money database creation program according to another aspect of the present invention is a computer, a plurality of past racehorse data, and broodmare data corresponding to the past racehorse data, stallion data, and lifetime Machine learning is performed by including winning prize money performance data, and a procedure for creating and recording prediction information data including predicted lifetime winning prize money data for each racehorse data is executed.

As described above, according to the present invention, a racehorse potential ability prediction program, a racehorse potential ability prediction method, and a racehorse that can predict information for quantifying and maximizing the potential competitive ability of a racehorse of potential ability prediction system can be provided.

Furthermore, the present invention can provide a stallion candidate presentation program, a stallion candidate presentation method, and a stallion candidate presentation system for presenting an optimum stallion to a broodmare.

1 is a schematic diagram of a system according to Embodiment 1; FIG. FIG. 4 is a diagram showing an example of an input screen of a customer computer CS in the system according to the first embodiment; FIG. 3 is an image diagram of a screen when a racehorse search is selected in FIG. 2 ; 8 is a diagram showing an example of a screen showing output results in the system according to the first embodiment; FIG. In the system according to Embodiment 2, it is a diagram showing an example of an input screen of the customer computer CS. FIG. 6 is an image diagram of a screen when a broodmare search is selected in FIG. 5 . FIG. 10 is a diagram showing an example of a screen showing an output result in the system according to the second embodiment;

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. However, the present invention can be embodied in many different forms, and should not be construed as being limited to the examples specifically shown in the following embodiments.

(Embodiment 1)
(Racehorse Potential Competitive Ability Prediction System)
A racehorse potential competitive ability prediction system according to this embodiment (hereinafter referred to as "this system" in this embodiment) S is (1) a procedure for inputting racehorse data, based on the input racehorse data , a procedure for obtaining and displaying prediction information data including predicted lifetime winnings data, and a computer C1 storing a potential competitiveness prediction program for a racehorse for executing the above; and (2) a plurality of past racehorse data. , and machine learning including broodmare data, stallion data, and lifetime prize money performance data corresponding to past racehorse data, and prediction information including predicted lifetime prize money data for each racehorse data and a computer C2 in which is recorded a predicted lifetime win prize database creation program for executing a procedure of creating and recording data. FIG. 1 is a schematic diagram of a system that implements the system S. As shown in FIG.

From the point of view of explanation and the point of view of more efficiently providing the system, the computer C1 and the computer C2 may be the same computer. The connection is preferably made through an electric communication line W.

In addition, in this system S, a customer computer CS exists as a customer using this system, and is in a state of being connectable through an electric communication line W as in the above case.

(Computer in which a racehorse's potential competitive ability prediction program is recorded)
Here, each component of the system S will be specifically described. First, as described above, the system S executes the procedure of inputting racehorse data, and the procedure of acquiring and displaying predicted information data including predicted lifetime prize money data based on the inputted racehorse data. It has a computer C1 in which a racehorse potential competitive ability prediction program (hereinafter referred to as "this prediction program" in this embodiment) is recorded.

Here, the "computer" is a mechanical device that can be driven by power supply and can perform predetermined processing. A memory such as RAM that can temporarily record data, a recording medium such as a hard disk or flash memory that can stably record data for a predetermined period, an input device that can perform predetermined input such as a keyboard or mouse , a bus connecting them, and a display device such as a liquid crystal monitor for displaying the results of the desired processing. This computer can include so-called ordinary desktop personal computers, laptop computers, etc., but in some cases, so-called smart phones, tablet terminals, etc., which are miniaturized by integrating an input device and a display device, etc., can also be included. can. In the case of this computer, the same applies. Therefore, explanation of the terms in each place is omitted except for special cases.

As described above, in the computer C1, the prediction program is recorded in a recording medium such as a hard disk. This prediction program can be temporarily read into a recording medium such as a RAM and executed by a user's desired operation to realize the above procedure. That is, the prediction program can realize a predetermined method by being executed. Specifically, it is possible to provide a racehorse potential competitive ability prediction method (hereinafter referred to as "this prediction method") that includes the above-described predetermined procedure.

The form of the "program" is not limited. And it may be an installation type that can be executed for the first time by installing it, but the computer C1 holds the program, and the web service or application that is displayed while performing predetermined processing while being read by the browser on the customer computer CS. A so-called web service type, such as a web service in which necessary data is transmitted to and received from the computer C1 or the computer C2 via a network such as the Internet while being installed in the computer CS, is preferable from the point of view of widespread use. If an application is installed in the customer computer CS to directly transmit and receive data to and from the computer CS, this corresponds to the case where the computer C1 functions as the customer computer CS.

(Prediction method)
First, as described above, the present prediction method realized by the present prediction program consists of (1-1) a procedure for inputting racehorse data, (1-2) based on the input racehorse data, predicted lifetime prize money data a procedure for obtaining and displaying prediction information data including

(1-1) The procedure for inputting racehorse data in this prediction method is not limited, but for example, a procedure performed by transmitting and inputting desired racehorse data from the customer computer CS. becomes. FIG. 2 shows an example of a screen input by the customer computer CS.

Here, "racehorse data" is data that includes information about racehorses, and more specifically, it is intended to predict how active a racehorse will be if it participates in a race from now on. Refers to data that includes information for identifying a particular racehorse. Information included in this racehorse data is not limited to the above, but for example, pedigree registration number (pedigree registration number data), horse name (horse name data), date of birth (date of birth data) and combinations of these information, including but not limited to.

The procedure for inputting the racehorse data may also include a procedure for searching for the racehorse data. Specifically, a plurality of stallion data, a plurality of broodmare data, a plurality of date of birth data, a plurality of horse name data, etc. are recorded in advance, and displayed on a computer display device, for example, a customer computer CS. It is also preferable to execute a procedure for searching, such as displaying racehorse data that can be candidates on the display device and selecting it according to the operation of the customer who operates the display device. As a result, there is an advantage that a target racehorse can be easily selected even if the pedigree registration number or the like of the racehorse is not necessarily known. An example of this case is shown in FIG. This figure is an image diagram of the screen when the racehorse search is selected in FIG.

In addition, (1-2) in the present prediction method, based on the input racehorse data, the procedure for acquiring and displaying prediction information data including predicted lifetime prize money data is specifically the above procedure (1-1 ), the computer C1 connects to the computer C2, acquires prediction information data including the predicted lifetime prize money data recorded in advance, and predicts the desired target including the obtained predicted lifetime prize money data. This is the procedure for displaying information data. This desired object may be his own computer C1, but it may also be the display device of the customer's computer CS where he originally entered the racehorse data.

Here, "predicted lifetime prize money data" is data recorded corresponding to each racehorse data, and refers to numerical data including information on the prize money that the racehorse is expected to earn in its lifetime. .

The details of this "predicted lifetime prize money data" will be clear from the description below, but it may be data that includes only comprehensive information on the amount of money. It is preferable that the data contain information that sums up the information. By doing so, it becomes possible to examine more detailed contents.

In addition, the "prediction information data" includes the above-described predicted lifetime win prize money data, but may also include data including various other information. Specifically, it may include, but is not limited to, "aptitude assessment data" and "potential assessment data".

Here, "aptitude evaluation data" is data that includes evaluation information regarding the aptitude of each racehorse. can do. By including exhaustive data on racehorses, users (including customers) can make more accurate information decisions.

In addition, here, "potential evaluation data" is data that includes evaluation information regarding the potential of a racehorse, specifically, race first start time, race retirement time, stamina evaluation, speed evaluation, constitution evaluation, Growth evaluation and the like can be exemplified. By including exhaustive data on racehorses, users (including customers) can make more accurate information decisions.

By the way, in this method, the prediction information data may be created when the computer C2 receives the request from the computer C1 and outputs the result to the computer C1. It is preferable that this system can be realized simply and quickly by recording the data as a database. That is, the procedure for acquiring and displaying prediction information data includes (2-1) recording a plurality of racehorse data and prediction information data corresponding to each of the plurality of racehorse data; It is preferable that the procedure is to acquire and display the corresponding prediction information data.

In this method, although the output of the results is not limited, it is possible to input the racehorse data and display the results on the screen of the computer used by the person who desires the results, specifically the customer computer CS. preferable.

Although the method for recording this prediction information data is not limited, it is preferable to use machine learning. By applying machine learning, it is possible to process information including more multidimensional viewpoints and obtain accurate lifetime win winnings data. An example of a screen displayed on the customer computer CS is shown in FIG.

Here, the data used in machine learning is not limited, but a plurality of past racehorse data, pedigree data recorded corresponding to each of the plurality of past racehorse data, lifetime winning prize money data , producer data, place of production data, date of birth data, coat color data, market data, age data at the time of transaction, transaction price data, race result data, horse body image data, etc., but not limited thereto.

Here, "past racehorse data" is racehorse data that is different from the "racehorse data" to be predicted, and is racehorse data that is used as data for machine learning. ”, and in other respects there is no significant difference from the above racehorse data. From this point of view, the same information as the above "racehorse data" can be included.

Here, "pedigree data" is data that includes information on the pedigree of the relevant racehorse, for example, broodmare (mother), stallion (father), mother of mother, father of mother, mother of father, father's Father, mother's mother's mother, mother's mother's father, mother's father's mother, mother's father's father, father's mother's mother, father's mother's father, father's father's mother, father's father's father Information on pedigree of the third degree can be exemplified, but is not limited to this.

In addition, "lifetime prize money data" here literally means data that includes information on the amount of prize money that the past racehorse has won in its lifetime, and data that includes information on the races it has entered and the prize money it has won in those races. It is preferable to be the sum of the above for more detailed examination. In this case, it is obtained by totaling the data including the prize information recorded in the race result data. In addition, when the past racehorse data is an active racehorse, this value will be updated at any time.

Also, "producer data" is literally data that includes information about the person who produced the racehorse. Of course, this data may also be recorded in association with horses such as the father and mother in the pedigree data.

Further, "production site data" is literally data including information on the place where the racehorse was bred. Of course, this data may also be recorded in association with each horse such as the father and mother in the pedigree data.

Further, "date of birth data" is literally data including information on the date of birth of the racehorse. Of course, this data may also be recorded in association with horses such as the father and mother in the pedigree data.

In addition, "coat color data" is literally data including information about the date of birth of the racehorse. Of course, this data may also be recorded in association with horses such as the father and mother in the pedigree data.

"Market data" is literally data containing information about the market in which the racehorse is traded. Of course, this data may also be recorded in association with horses such as the father and mother in the pedigree data.

Also, the “age data at the time of transaction” is literally data that includes information on the age at the time the racehorse is traded. Of course, this data may also be recorded in association with horses such as the father and mother in the pedigree data.

Also, "transaction price data" is literally data that includes information on the price when the racehorse is traded. Of course, this data may also be recorded in association with horses such as the father and mother in the pedigree data.

Further, "horse body image data" literally means data containing information about the appearance of the racehorse, and more specifically, image data obtained by photographing the horse body. Of course, this data may also be recorded in association with horses such as the father and mother in the pedigree data. The horse's body image may be data at a specific age, or image data at a plurality of ages may be recorded by including age information.

Also, "race result data" literally means data including information about the race result of the racehorse. Here, it is preferable to include race conditions and the like in the information on race results. The information about the race result is not limited, but for example, date (date data), weather (weather data), racecourse (racecourse data), racecourse condition (racecourse condition data), race number (race number data), race name (race name data), grade (grade data), race class (race class data), race conditions (race condition data), turf dirt classification (turf dirt classification data), right-left turn (left-right turn data) ), distance (distance data), inside and outside (inside and outside data), prize money (main prize money data), additional prize money (additional prize money data), frame number (frame number data), horse number (horse number data), order of finish (order of finish data ), burden weight (load weight data), time (time data), arrival difference (arrival difference data), popularity (popularity data), odds (odds data), jockey (jockey data), etc. can be exemplified. is not limited to Also, it is preferable that a large number of race results be recorded for one racehorse. In addition, it is preferable to add this data as needed for active racehorses. When the main prize and the additional prize are recorded separately, it is preferable to treat the total prize as the prize money data.

In the above, it is preferable to modify and record the prize money data including the information of the prize money such as the main prize money or the additional prize money. While this system predicts prize money to be won in the future, there are many cases where the current situation and the prize money of the race are different. In such a case, by correcting this data or the information on the prize money of the race in advance, it is possible to predict the expected prize money more accurately.

It is also preferable that the "race result data" include not only information on each race, but also information on the date and time of the first race and the timing of retirement from the race.

Here, machine learning is a technique that uses so-called artificial intelligence to find regularity and rules from input data indicating a target and to improve judgment by repeating learning. With respect to artificial intelligence, TensorFlow® provided by Google® is suitable, but not limited to, but not limited to.

In addition, specific algorithms of machine learning include linear regression by regression, logistic regression, support vector machine, decision tree by tree, regression tree, random forest, gradient boosting tree, naive Bayes by Bayes, AR, MA, (S) ARIMA model, state space model, k nearest neighbor method by clustering, boosting, bagging, perceptron, deep learning by neural network, convolutional neural network, recursive neural network, residual network, etc. can be exemplified. is not limited to In addition, although not limited, in the case of a method such as deep learning using the above neural network modeled on the human brain, a cloud server such as Google (registered trademark) Cloud ML Engine (registered trademark) is used. is preferred.

As described above, as is clear from the above description, in this system, while mechanical learning is performed using a large amount of data related to past racehorses, this data is used in advance for races that are scheduled to be traded on the market in order to run in future races. By entering horse data, you can obtain information for quantifying and maximizing the potential competitive ability of a racehorse, such as how much prize money the racehorse to be traded can earn. be able to

By the way, when actually providing services to customers through electric communication lines, there are cases where money is exchanged. Specifically, it may be necessary to pay for the provision of the above data. In such cases, it is useful to identify the customer and determine whether the customer is currently available for service. An example of this case is shown below.

First, for the customer computer CS, (0-1) a procedure for requesting the input of customer identification number data and its password data, (0-2) authentication based on the input customer identification number data and password data. (0-3) If the authenticated customer identification number data is valid, move to the screen for entering the racehorse data described above, and if it is not valid, re-enter the customer identification number data and password Preferably, there is a procedure for requesting input of data or for terminating the process. By doing so, it is possible to provide appropriate services.

In this case, in the procedure (0-2), it is not only a simple check whether the customer identification number data and the password data correspond to each other, but also whether the customer has effectively paid the prescribed amount. It is also preferable to determine customer validity as to whether or not By doing so, it is possible to provide appropriate services. In order to implement this procedure, the computer C1 or C2, preferably the computer C1, preferably stores customer identification number data, its password data, and customer validity data as a database.

In this case, it is preferable that the customer performs the registration procedure in advance, that the computer C1 notifies the result of the registration procedure, and that the customer pays a predetermined fee in advance (adopting a customer pre-registration system). Although it is a mode, depending on the case, money may be given and received each time the customer wants to obtain data. In this case, in place of or in addition to the customer identification number data and password data, input of credit data including credit information on credit card and transfer is requested, this data is output to a predetermined financial institution, and the response is valid. If it is determined that the data is correct, the screen may be shifted to the input screen for the racehorse data.

As described above, the system S can predict the information for quantifying and maximizing the potential competitive ability of the racehorse, the potential ability prediction program of the racehorse, the potential ability prediction method of the racehorse, and the race A horse potential prediction system can be provided.

(Embodiment 2)
(Sale candidate presentation system)
According to the system according to the first embodiment, the potential ability of a racehorse can be predicted with high reliability. By using this, it becomes possible to provide a new system, more specifically, a system for presenting stallion candidates (hereinafter referred to as "present presentation system"). A specific description will be given below. In this embodiment, only the relationship between data to be transmitted (output) and received (input) is different, and the description of the same and overlapping portions as in the first embodiment will be omitted.

The outline of this presentation system S is the same as that in FIG. A computer C1 in which a stallion candidate presentation program for executing a procedure for acquiring and displaying prediction information data is recorded; (2) a plurality of past racehorse data and broodmare corresponding to the past racehorse data Data, stallion data, and lifetime winning prize money performance data are included, machine learning is performed, and a procedure for creating and recording prediction information data including predicted lifetime winning prize money data for each racehorse data is executed. and a computer C2 in which is recorded a predicted lifetime win prize database creation program for.

This presentation system S assumes racehorse breeders and owners as specific customers. It is used to predict whether a racehorse will be born.

In this presentation system S, as described above, (1-1) Procedure for inputting broodmare data, (1-2) Based on the input broodmare data, predictive information data including predicted lifetime prize money data is acquired. and displaying a stallion candidate presentation program recorded therein.

Here, "broodmare data" is, as is clear from the above description, data containing information for specifying a broodmare to be mated with a stallion. The broodmare data is not limited, but can be the same as the racehorse data in the first embodiment. For example, pedigree registration number (pedigree registration number data), horse name (horse name data ), date of birth (date of birth data), and combinations of these information.

In (1-1) of the presentation system S, basically, "racehorse data" in the first embodiment can be replaced with "broodmare data".

In addition, unlike the first embodiment, the present presentation system S includes (1-2) a procedure for acquiring and displaying prediction information data including predicted lifetime prize money data based on the input broodmare data. . Here, the definitions of "predicted lifetime prize money data" and "prediction information data" are the same as in the first embodiment.

However, in the present presentation system S, although the "prediction information data" is displayed based on the input broodmare data, there are a plurality of "stallion data" and racehorse data generated when mated with each of them. Display a plurality of sets of "prediction information data" in . As a result, in this presentation system, when a broodmare is specified, it becomes possible to evaluate with which stallion a racehorse with a larger lifetime prize money can be produced. In this case, FIGS. 5 and 6 show images of screens for inputting information to a customer's computer, and FIG. 7 shows images of a screen showing output results. FIG. 6 is an image diagram of the screen when the search means is employed in FIG.

There are a large number of stallions, and it is not impossible to calculate and display all of them. is preferably selected and displayed, and more preferably displayed in descending order of predicted lifetime earnings. By doing so, it is possible to provide information that is easier for the customer to judge.

Therefore, in the present presentation system S, the prediction information data is recorded in advance by machine learning using artificial intelligence in the same procedure as in the first embodiment, and when there is an input from the computer C1, the result In order to display, consider the possibility of mating each multiple broodmare with multiple stallions, give the identification number data of the child between the stallion and the broodmare, and each identification number First, it is preferable to create prediction information data and record it in advance.

As described above, in addition to the above-described Embodiment 1, the presentation system S focuses on the relationship between the broodmare and the stallion, and applies the above to present the optimum stallion to the broodmare. It is possible to provide a presentation program, a stallion candidate presentation method, a stallion candidate presentation system, and a predicted lifetime winning prize money database creation program used for these.

The present invention provides a racehorse potential prediction program, a racehorse potential prediction method, a racehorse potential prediction system, a stallion candidate presentation program, a stallion candidate presentation method, and a breed There is industrial applicability as a stallion candidate presentation system, and also as a predictive lifetime winning prize money database creation program used for these. The present invention promotes the improvement of operational efficiency in racehorse production, helps to produce racehorses with higher competitiveness, and activates transactions by providing information with high added value in racehorse trading and racehorse investment. It helps to make Furthermore, it can be used for providing information through electric communication lines such as the Internet and for the publishing industry, thereby contributing to the expansion of the horse racing industry.

Claims (3)

to the computer,
a procedure for entering racehorse data , including studbook number data and horse name data ;
A racehorse potential competitive ability prediction for executing a procedure for obtaining and displaying prediction information data including predicted lifetime winnings data , aptitude evaluation data, and potential evaluation data based on the input racehorse data. a program ,
The prediction information data includes a plurality of past racehorse data, pedigree data including broodmare data and stallion data corresponding to the past racehorse data, race performance data, and the prize money corresponding to the race performance data. A program for predicting the potential competitiveness of a racehorse created by performing machine learning including lifetime winning prize money performance data that is the sum of data and additional prize money data. A procedure for inputting racehorse data including pedigree registration number data and horse name data , and obtaining prediction information data including predicted lifetime winnings data , aptitude evaluation data and potential evaluation data based on the input racehorse data. a computer in which a program for predicting the potential competitiveness of a racehorse is recorded for executing the procedure for displaying
A plurality of past racehorse data, pedigree data including broodmare data and stallion data corresponding to the past racehorse data, race performance data, and prize money data and additional prize money data corresponding to the race performance data A procedure for performing machine learning including total lifetime prize money performance data, and creating and recording prediction information data including predicted lifetime prize money data, aptitude evaluation data and potential evaluation data for each racehorse data. A racehorse potential competitiveness prediction system comprising: a computer in which is stored a predicted lifetime winnings database generating program for executing: to the computer,
A plurality of past racehorse data, pedigree data including broodmare data and stallion data corresponding to the past racehorse data, race performance data, and prize money data and additional prize money data corresponding to the race performance data Perform machine learning including total lifetime earnings performance data, including predicted lifetime earnings data , aptitude assessment data and potential assessment data for each racehorse data including studbook number data and horse name data. A predictive lifetime winnings database creation program for executing a procedure for creating and recording predictive information data.

Images