• 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 Labour Economics
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• v.39 no.2
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• pp.113-139
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• 2016

The purpose of this study is to establish evaluation model that can explain marginal effects of baseball players of Korean Baseball Organization (KBO) on their team winnings in terms of productivity. We proposed econometric model with using variables that are provided from official homepage of KBO to overcome the complexity of mainly used productivity index: wins above replacement (WAR). Also, compare to the previous studies such as Scully(1974) or Krautmann(1999) that using limited indices of baseball stats, this study included 61 indices that are provided from official homepage of KBO. We estimated regression based WAR(RBWAR) by conducting panel regression with each team's statistics data of 2002 to 2014. As a results, RBWAR shows 0.869 correlation coefficient for batters and 0.882 for pitchers with WAR in 2014 that can be concluded that two indices shows similar results. From the results of estimation, we analyze the relationship between productivity and actual contract of free agent players in 2015 and it showed that teams have contracted reasonably.

• 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.

• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.30-36
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• 2022

This study analyzed the relationship between efficient pitchers and teams advancing to the postseason in Korean professional baseball through DEA. A total of 1,133 pitchers who threw more than one inning from the 2014 season to the 2018 season were selected for this study. For DEA analysis, input variables were selected as annual salary and inning output variables as Wins, Saves, and Holds and the number of efficient pitchers for each season was classified using the input-oriented BCC model. After that, it was divided into two groups based on joining the postseason or not, and the number of efficient pitchers was compared through a prop test. As a result of the analysis, the groups that advanced to the postseason in the rest of the season except for the 2014 and 2017 seasons had more efficient pitchers. Considering that the 2014 season recorded the highest WAR (Wins Above Replacement) at 183.56 compared to other seasons, most pitchers threw well, and in the 2017 season, they made more mistakes in pitching than in other seasons, but they performed well in batters. The results of this study have expanded the research field using efficiency analysis in professional baseball and can be used as useful data for practical research.

• 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.