• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.635-645
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• 2017

In this paper, we propose batting index prediction models of 2017. Due to the insufficiency of KBO pitchers data, batting index prediction models of 2016 has been developed based on elected eight batting index collecting the past three years data of MLB and KBO. It has been found that this prediction model fits well to both MLB and KBO, and the KBO model fits better than MLB in some cases. Using these prediction models, we analyzed and compared 2016's estimated values for the batting index of MLB and KBO. With the relation results between batting index prediction and batter's age for MLB and KBO, it can be determined that there is no relationship between the significant batting index and ages.

• 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.

• 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.3
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• pp.625-633
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• 2017

Fielding Independent Pitching (FIP) is a statistic that measure pitcher performance by eliminating plate appearance outcomes that involve defensive play. FIP uses pitcher dependent outcomes such that walks, strikeouts, hit by pitches, and home runs allowed. The FIP equation derived from linear weights uses three coefficients 13, 3, -2 for evaluating Major League Baseball pitchers. However, these coefficients derived from run value of major league baseball are not suitable to Korea Baseball Organization pitchers due to baseball circumstances. In this study, new FIP called kFIP for Korea Baseball Organization pitchers are provided. We recalculate coefficients and get 14, 3, -1 for evaluating Korean Baseball pitchers. As a result, kFIP is statistically significantly better than FIP at predicting pitcher ERA in KBO League.

• 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.

• The Korean Journal of Applied Statistics
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• v.29 no.2
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• pp.321-330
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• 2016

Run expectancy (RE) is the mean number of runs scored from a specific base runner/outs situation of an inning to the end of the inning. Win expectancy (WE) is the probability that a particular team will win the game at a specific game state such as half-inning, score difference, outs, and/or runners on base. In this paper, we derive RE and WE for the Korea Baseball Organization (KBO) League based on six-year data from 2007 to 2012 using a Markov chain model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.177-185
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• 2020

Recently, the popularity of professional baseball is increasing day by day, and it has data related to professional baseball on various portal sites. If you want to increase the popularity of professional baseball and produce results through analysis using relevant data, you have the advantage of accessing professional baseball. In this paper, three analyzes were conducted using data related to professional baseball. Therefore, in this paper, the trend related to the number of articles retrieved from a specific site of a professional baseball team was examined, and the correlation between professional baseball scores and the number of spectators was analyzed. Finally, we analyzed the current status of professional baseball batting average and on base percentage in 2016 and 2017.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1095-1106
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• 2016

The quantile regression method proposed by Koenker et al. (1978) focuses on conditional quantiles given by independent variables, and analyzes the relationship between response variable and independent variables at the given quantile. Considering the linear programming used for the estimation of quantile regression coefficients, the model fitting job might be difficult when large data are introduced for analysis. Therefore, dimension reduction (or variable selection) could be a good solution for the quantile regression of large data sets. Regression tree methods are applied to a variable selection for quantile regression in this paper. Real data of Korea Baseball Organization (KBO) players are analyzed following the variable selection approach based on the regression tree. Analysis result shows that a few important variables are selected, which are also meaningful for the given quantiles of salary data of the baseball players.