• The Korean Journal of Applied Statistics
• /
• v.29 no.7
• /
• pp.1271-1281
• /
• 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
• /
• v.39 no.2
• /
• pp.113-139
• /
• 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
• /
• v.28 no.6
• /
• pp.1501-1509
• /
• 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
• /
• v.28 no.4
• /
• pp.863-874
• /
• 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 the Korean Data and Information Science Society
• /
• v.28 no.2
• /
• pp.317-326
• /
• 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.