• The Journal of Bigdata
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• v.5 no.2
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• pp.77-84
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• 2020

In this study, we conducted a study on the win-loss predicton analysis of korean professional baseball by artificial intelligence models. Based on the model, we predicted the winner as well as each team's final rank in the league. Additionally, we developed a website for viewers' understanding. In each game's first, third, and fifth inning, we analyze to select the best model that performs the highest accuracy and minimizes errors. Based on the result, we generate the rankings. We used the predicted data started from May 5, the season's opening day, to August 30, 2020 to generate the rankings. In the games which Kia Tigers did not play, however, we used actual games' results in the data. KNN and AdaBoost selected the most optimized machine learning model. As a result, we observe a decreasing trend of the predicted results' ranking error as the season progresses. The deep learning model recorded 89% of the model accuracy. It provides the same result of decreasing ranking error trends of the predicted results that we observe in the machine learning model. We estimate that this study's result applies to future KBO predictions as well as other fields. We expect broadcasting enhancements by posting the predicted winning percentage per inning which is generated by AI algorism. We expect this will bring new interest to the KBO fans. Furthermore, the prediction generated at each inning would provide insights to teams so that they can analyze data and come up with successful strategies.

• Journal of Industrial Convergence
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• v.18 no.4
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• pp.61-66
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• 2020

Recently, attempts have been made to use data to operate games, seasons, and teams in professional baseball. Therefore, in this study, we collected baseball game records and analyzed the relationship between on-base rate and pitching count induction, and this was defined as the third record for non-game factors such as discomfort index, which includes the weather application data. When the discomfort index was over 75, the pitcher's induction of pitching was high, and when the discomfort index was less than 69.9, the on-base rate was high, but when the discomfort index was 70 or more and less than 75, the batter's on-base performance was the lowest. Through the results of the study, it could be inferred that the discomfort index, the batter's on-base rate, and the number of induction pitches are related, and that it is highly likely to be related to the pitcher's performance. Through this study, we could see the possibility of defining a cumulative/ratio record defined as the primary record and a saver metric defined as the secondary record, and a third, tertiary record linking data outside the game.

• Journal of the Korean Data and Information Science Society
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• v.23 no.2
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• pp.285-298
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• 2012

This research deals with a relationship between the performance of Korean professional baseball players and their annual salaries. It is based on the sabermetrics, which measures the performance of baseball batters in a refined way. We collect the records of batters of eight professional baseball clubs during the season 2009 and 2010. Then, we calculate every index of the sabermetrics. Principal component analysis is used for examining the relationship between those indexes of sabermetrics and annual salary for the next year. In general, batters who show higher performance get more salary. The result of this research can be useful in order to reach an agreement on salary between a player and his club partner.

• Journal of Korea Entertainment Industry Association
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• v.15 no.2
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• pp.123-135
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• 2021

The data processing of this study is focused on keywords related to 'Corona 19 and professional baseball' and 'Corona 19 and professional baseball no spectators', using text mining and social network analysis of textom program to identify problems and view quality. It was used to set the variable of For quantitative analysis, a questionnaire on viewing quality was constructed, and out of 270 survey respondents, 250 questionnaires were used for the final study. As a tool for securing the validity and reliability of the questionnaire, exploratory factor analysis and reliability analysis were conducted, and IPA analysis (importance-satisfaction) was conducted based on the questionnaire that secured validity and reliability, and the results and strategies were presented. As a result of IPA analysis, factors related to the image (image composition, image coloration, image clarity, image enlargement and composition, high-quality image) were found in the first quadrant, and the second quadrant was the game situation (support team game level, support player game level, star). Player discovery, competition with rival teams), game information (match schedule information, player information check, team performance and player performance, game information), interaction (consensus with the supporting team), and some factors appeared. The factors of commentator (baseball-related knowledge, communication ability, pronunciation and voice, use of standard language, introduction of game-related information) and interaction (real-time communication with the front desk, sympathy with viewers, information exchange such as chatting) appeared.

• 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 Korean Data and Information Science Society
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• v.26 no.1
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• pp.197-207
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• 2015

In baseball game, the hitting ability of batter is frequently assessed by a batting average, a run batted in, a home run, a run scored, an on-base percentage, etc. Recently, more comprehensive indicators such as OPS, ISO, SECA, TA, RC and XR are often used. But, these measures generally shows large deviations since they are calculated from the data for a certain period of time, and they are not an estimate of a population parameter, either. In this paper, we will presume the pure hitting ability of the korea professional baseball players as a parameter which is depend upon at bat. We will estimate the parameter by using the Bayesian method.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.309-316
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• 2017

In baseball, estimation of winning percentage is critical and many studies for this topic have been actively performed. Pairwise winning percentage estimation using Pythagorean winning percentages of individual teams against other individual teams has the property that the sum of estimated winning percentage totals must be a constant. In this paper, we consider two types of pairwise estimation including linear formula and Pythagorean formula to the Korean baseball data of seasons from 2013 to 2016 under the criterions of RMSE and MAD. In conclusion, pairwise Pythagorean methods have the smaller RMSE and MAD than traditional Pythagorean methods. We suggest the optimal pairwise Pythagorean formula with a fixed exponent. Also we show that there are very little differences of RMSE and MAD between variation in exponent values.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.317-326
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• 2017

In this paper, we investigate the effects of performance and non-performance variables attributed to Korean professional baseball pitchers on annual salary by the records about pitchers between 2010 and 2016. We select the variables in reference to previous research related to this topic. The models are then estimated using linear regression model. For pitchers, age, experience in the league, year, eligibility for free agency, the number of wins, WAR, the number of innings pitched, the number of games, the number of saves, the number of games started, and type of baseball team have a statistically significant effect. Among the notable factors, affecting pitchers salaries are largely measure of starting pitchers. Pitcher sabermetrics indexes were poorly reflected on annual salary. The model presented here can be used to remove any unobjective salary differences for Korean professional baseball pitchers.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.335-337
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• 2019

본 연구에서는 키넥트와 아두이노 초음파센서를 이용하여 야구 경기 시 발생하는 센서 데이터를 획득하여 스트라이크 판단이 가능한 알고리즘 및 디바이스를 개발하였다. 개발된 디바이스는 야구 경기장 홈플레이트로 사용하며 스트라이크, 볼의 경우에 대해 판단하도록 하였다. 판단에는 스트라이크 존을 측정하기 위해 키넥트의 skeleton tracking 예제로 관절을 측정해 좌표를 알아내고 아두이노 초음파센서를 사용하여 스트라이크를 판단하도록 했다.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.119-126
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• 2023

In this paper, a new model was presented to objectively evaluate the defense ability of defenders in Korean professional baseball. In the proposed model, using Korean professional baseball game data from 2016 to 2019, a representative defender was selected for each team and defensive position to evaluate defensive ability. In order to evaluate the defense ability, a method of calculating the defense range for each position and dividing the calculated defense area was proposed. The defensive range for each position was calculated using the Convex Hull algorithm based on the point at which the defenders in the same position threw out the ball. The out conversion score and victory contribution score for both infielders and outfielders were calculated as basic scores using the defensive range for each position. In addition, double kill points for infielders and extra base points for outfielders were calculated separately and added together.