• Journal of Korean Society of Archives and Records Management
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• v.16 no.3
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• pp.157-177
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• 2016

This study proposes an effective direction for operating the "Korea Baseball of Fame" based on baseball records. To clarify problems, a literature review on the case analysis of the "Hall of Fame" of the United States and Japan, an assortment and management of Korean baseball records, and a consultation with officials who work in the baseball industry were progressed. In conclusion, this study suggested building an archive database to operate the "Korea Baseball Hall of Fame" effectively. First, archives will be collected, and then managed and utilized at the "Korea Baseball Hall of Fame." Second, to preserve the memories of baseball heroes, an oral archive will be constructed. Third, baseball records will be assorted and stored in a database.

• Journal of Korean Ophthalmic Optics Society
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• v.15 no.1
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• pp.87-97
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• 2010

Purpose: The purpose of this study is to investigate the effects of sports vision training on baseball player's visual performance and baseball records. Methods: All subjects were 21 males of high school baseball players, and they participated on eight weeks of sports vision training program. Pre- and post- test results were obtained for static and dynamic visual acuity, static and dynamic stereo acuity, distance and near phoria, fusional reserves, near point of convergence, contrast sensitivity, visual-reaction time. Results: Statical analysis indicated significant improvement in most of mentioned visual variables and baseball records (p<0.001). Conclusions: It can be concluded that the sports vision training program improves visual skills of baseball players, which could lead to improvement in the baseball records. Vison training will be a promotor for baseball player to enhance their performance if proper test instruments and training course is supplied.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.539-549
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• 2008

Most important thing in professional baseball game among all kinds of sports is the winning. Both coaches and players collected and analyzed lots of game data to get a victory. In this paper, batting data are analyzed so as to represent informations of hitting direction visually. This method could be provided a lot of useful information about hitting direction of a specific batter or a team to not only coaches, players but also the audience.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.612-614
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• 2019

In this study, amateur baseball team leaders studied ways to train student baseball team players through records management. To this end, a system was developed that could apply the formula for obtaining various secondary records or savermetrics data. The team distributed the information to three leaders of the student baseball team and studied the training guidelines through the target group interface. Through the records, students were able to increase motivation and make sure that all the players were faithful to their roles.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.6
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• pp.693-698
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• 2003

Every baseball game generates various records and on the basis of those records, win/lose prediction about the next game is carried out. Researches on win/lose predictions of professional baseball games have been carried out, but there are not so good results yet. Win/lose prediction is very difficult because the choice of features on win/lose predictions among many records is difficult and because the complexity of a learning model is increased due to overlapping factors among the data used in prediction. In this paper, learning features were chosen by opinions of baseball experts and a heuristic function was formed using the chosen features. We propose a hybrid model by creating a new value which can affect predictions by combining multiple features, and thus reducing a dimension of input value which will be used for backpropagation learning algorithm. As the experimental results show, the complexity of backpropagation was reduced and the accuracy of win/lose predictions on professional baseball games was improved.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.653-659
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• 2015

The Pythagorean formula for baseball postulated by James (1982) indicates the winning percentage as a function of runs scored and runs allowed. However sometimes, the Pythagorean formula gives a less accurate estimate of winning percentage. We use the records of team vs team historic win loss records of Korean professional baseball clubs season from 2005 and 2014. Using assumption that the difference between winning percentage and pythagorean expectation are affected by unusual distribution of runs scored and allowed, we suppose that difference depends on mean, standard deviation, and coefficient of variation of runs scored per game and runs allowed per game, respectively. In conclusion, the discrepancy is mainly related to the coefficient of variation and standard deviation for run allowed per game regardless of run scored per game.

• The Korean Journal of Applied Statistics
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• v.33 no.2
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• pp.171-184
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• 2020

Major League Baseball (MLB) records and releases the trajectory data for every baseball pitch, called the PITCHf/x, using three high-speed cameras installed in every stadium. In a previous study, the quality of the pitch was assessed as the expected number of bases yielded using PITCHf/x data. However, the number of bases yielded does not always lead to baseball scores, or runs. In this paper, we assess the quality of a pitch by combining baseball analytics metric Run Expectancy and Run Value using a Random Forests model. We compare the quality of pitches evaluated with Run Value to the quality of pitches evaluated with the expected number of bases yielded.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.978-984
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• 2020

In this study, the correlation between sports records and weather data was analyzed using the big data analysis method. To this end, data was collected by API and crawling, data was processed, statistics were performed, and data visualization was performed. The subject of this study was a player who entered the regular at-bat among outfielders in the 2019 KBO League. In addition, meteorological data were analyzed by using the unpleasant index and above 70 and below 70. As a result of the study, in the various hitting indicators, which are the records that pitchers intervene, the higher the unpleasant index, the better the outfielder's record, but pitchers, walks, pitches, pitching success rates, pitches per turn, pitches per game From the records of the back, it was found that the outfielder made the pitcher difficult. It is expected that this study will help the development of the sports data industry and the performance of baseball players, baseball teams, and coaching staff.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.41-47
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• 2019

In this paper, we propose a new batter evaluation model that reflects the skill of the opponent pitcher in Korean professional baseball. The model consists of evaluation factors such as Run Value, Contribution Score and Ball Consumption considering the pitcher grade. These evaluation factors are calculated as different data. In order to include the evaluation factors having different characteristics into one model, each evaluation factor is weighted and added. The genetic algorithms were used to calculate the weights, and the data were based on the 2016 records of Korea Professional Baseball and the salary data of the players of 2017. As a result of calculation of the weight, the weight of the Run Value was high and the weight of the Contribution Score was very low. This means that when calculating the annual salary, it reflects much of the expected score according to the batting result of the batter. On the other hand, the contribution score indicating the degree to which the batting result contributed to the victory of the team according to the state of the economy is not reflected in the salary or point system.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.1
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• pp.8-17
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• 2014

In this research, we employed various data mining techniques to build predictive models for win-loss prediction in Korean professional baseball games. The historical data containing information about players and teams was obtained from the official materials that are provided by the KBO website. Using the collected raw data, we additionally prepared two more types of dataset, which are in ratio and binary format respectively. Dividing away-team's records by the records of the corresponding home-team generated the ratio dataset, while the binary dataset was obtained by comparing the record values. We applied seven classification techniques to three (raw, ratio, and binary) datasets. The employed data mining techniques are decision tree, random forest, logistic regression, neural network, support vector machine, linear discriminant analysis, and quadratic discriminant analysis. Among 21(= 3 datasets${\times}$7 techniques) prediction scenarios, the most accurate model was obtained from the random forest technique based on the binary dataset, which prediction accuracy was 84.14%. It was also observed that using the ratio and the binary dataset helped to build better prediction models than using the raw data. From the capability of variable selection in decision tree, random forest, and stepwise logistic regression, we found that annual salary, earned run, strikeout, pitcher's winning percentage, and four balls are important winning factors of a game. This research is distinct from existing studies in that we used three different types of data and various data mining techniques for win-loss prediction in Korean professional baseball games.