• 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.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1271-1281
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• 2016

Wins above replacement (WAR) is one of the most widely used statistic among sabermatrics statistics that measure the ability of a batter in baseball. WAR has a great advantage that is to represent the attack power of the player and the base running ability, defensive ability as a single value. In this study, we proposed a hitter ability index using the sabermetrics statistics that can replace WAR based on Korea Baseball Record Data of the last three years (2013-2015). First, we calculated Batter ability index through the arithmetic mean method, the weighted average method, principal component regression and selected the method that had high correlation with WAR.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.863-874
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• 2017

Wins above replacement (WAR) is the most commonly used statistics of the many sabermetrics that measure baseball players' abilities. The advantage of a WAR is that it enables to compare performances of players even though they have different roles such as pitcher and hitter. However, WAR is difficult to obtain with common records. Thus, in this paper, we have calculated the sabermetrics variable based on Korean professional baseball records for the past three years (2014-2016). Using these variables, we suggest starting pitcher ability index that can replace WAR. Starting pitcher ability index was calculated by means of arithmetic mean, weighted average and principal component regression. Then, compared to the WAR, the most relevant method was selected, which would be useful to identify for the starting pitcher ability.

• 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 the Korean Data and Information Science Society
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• v.27 no.3
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• pp.677-687
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• 2016

Among lots of sabermetric statistics for baseball batters' ability, the wins above replacement (WAR) is the most popular statistic in MLB. However, there exists a difficulty applying WAR to KBO, since KBO data do not have position adjustment, league adjustment and park factor which are essential in calculating WAR. In this paper, using five statistics for both KBO and MLB qualified batters, we propose hitting ability index (HAI), an alternative sabermetric indices to represent batters' ability. Comparing HAI with WAR of MLB batters, we evaluate the validity of HAI and then applied HAI to 2015 KBO data in which HAI is analyzed statistically with respect to different teams, ages, and positions. Moreover, the linear relationship between KBO batter's HAI and their annual salary is discussed. Grouping 46 KBO batters based on confidence region of the regression model for annual salary, we also statistically investigate batter's annual salary in these groups with respect to several factors.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1501-1509
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• 2017

Wins above replacement (WAR) is the most commonly used statistics of the sabermetrics that measure baseball players' abilities. The advantage of a WAR is that it enables to compare performances of players even though they have different roles such as pitcher and hitter. However, WAR is difficult to obtain with common records. Thus, a past studies (Lee and Kim, 2016) suggested the batting ability index to determine the ability of the batter focused on the sabermetrics statistics WAR. In this paper, we selected the best hitter with applying Korea baseball 2016 data based on a proposed model and then observed a total raking of others according to BAI. We are assured that BAI is very excellent statistics through comparing BAI and WAR which is in the spotlight in evaluating performances of players.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.999-1005
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• 2016

The advent of big data brings the opportunity to answer many open scientic questions but also presents some interesting challenges. Main features of contemporary datasets are the high dimensionality and massive sample size. In this paper, we give an overview of major challenges caused by these two features: (1) noise accumulation and spurious correlations in high dimensional data; (ii) computational scalability for massive data. We also provide applications of big data in various fields including forecast of disasters, digital humanities and sabermetrics.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.321-322
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• 2018

빅데이터 분석은 스포츠에서 다양한 분야에서 사용되고 있다. 야구산업에서도 세이버 메트릭스를 활용하여 전술 훈련, 개인 훈련 등 다양한 방면으로 활용되고 있다. 본 논문에서는 기존의 연구인 빅데이터 분석과 게임이론을 활용한 축구선수 영입 모델을 야구에 적용킨 시뮬레이션을 진행하고 합리적인 의사결정 모델을 제안한다.

• Journal of the Korean Data and Information Science Society
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• v.26 no.4
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• pp.865-874
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• 2015

This research is to comprehensively evaluate offensive abilities of baseball players who are expected to produce as many runs as possible by their hitting and running. To this end, we establish a simulation program to obtain the so-called scoring index of an individual player. The scoring index of a player is defined as an expected number of runs scored by an imaginary team that is composed of nine copies of the player. As a simulation input, we use 2014 season data of Korean pro-baseball. As a result, we present the scoring indices of top 10 players, 9 Korean pro-baseball teams, and overall 2014 season. The scoring index can serve as a comprehensive evaluation of offensive ability of a player or a team, selection of players for a (national) team or for a starting line-up, estimation of player's worth, and so on.

• 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.