• The Korean Journal of Applied Statistics
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• v.26 no.4
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• pp.649-659
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• 2013

We use a Markov chain model to analyze the Korean Baseball League. We derive the distributions of the number of runs scored and the number of batters that complete their turn at bat in a baseball game using the time inhomogeneous Markov chain. The model is tested with real data produced from the 2011 Korean Baseball League.

• 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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.299-303
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• 2008

In this paper, we discuss the schedule problems for Korean Professional Baseball League (KPBL) and propose approaches to solve these problems by applying Integer Programming. A schedule in a sport league must satisfy lots of constraints on timing such as organizational, attractiveness, and fairness requirements. Organizational requirements cover a set of rules which have to guarantee that all the games can be scheduled according to the regulations imposed by Korean Baseball Organization (KBO). Attractiveness requirements focus on what stadium visitors, television spectators, and the clubs expect, that is, a varied, eventful, and exciting season. Fairness requirements have to guarantee that no team is handicapped or favored in comparison with the others. In addition to finding a feasible schedule that meets all the constraints, the problem addressed in this paper has the additional complexity of having the objective of minimizing the travel costs and every team has the balancing number of the games in home. We formalize the KPBL problem into an optimization problem and adopt the concept of evolution strategy to solve it. Using the method proposed, it is efficient to find better results than approaches developed before.

• The Korean Journal of Applied Statistics
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• v.33 no.2
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• pp.171-184
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• 2020

Major League Baseball (MLB) records and releases the trajectory data for every baseball pitch, called the PITCHf/x, using three high-speed cameras installed in every stadium. In a previous study, the quality of the pitch was assessed as the expected number of bases yielded using PITCHf/x data. However, the number of bases yielded does not always lead to baseball scores, or runs. In this paper, we assess the quality of a pitch by combining baseball analytics metric Run Expectancy and Run Value using a Random Forests model. We compare the quality of pitches evaluated with Run Value to the quality of pitches evaluated with the expected number of bases yielded.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.653-661
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• 2016

In this paper, we provide a suitable optimal exponent in the generalized Pythagorean theorem and propose to use the logistic model & the probit model to estimate the winning rate in Korean professional baseball league. Under a criterion of root-mean-square-error (RMSE), the efficiencies of the proposed models have been compared with those of the Pythagorean theorem. We use the team historic win-loss records of Korean professional baseball league from 1982 to the first half of 2015, and the proposed methods show slight outperformances over the generalized Pythagorean method under the criterion of RMSE.

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.223-236
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• 2013

Various statistical classification methods to predict election to the Major League Baseball hall of fame of are implemented and their accuracies are compared. Seventeen independent variables are selected from the data of candidates eligible for the hall of fame and well-known classification methods such as discriminant analysis and logistic regression as well as the recently proposed Mahalanobis-Taguchi system(MTS). The MTS showed a better performance than the others in classification accuracy because it is especially efficient in cases where multivariate data does not constitute directionally geographical groups according to attributes.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1139-1148
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• 2011

Team standings in the regular professional baseball league should be determined based on a reasonable criterion; however, an unreasonable Japanese method is being used in Korea as of 2011. In this paper, we suggest a new method of computing the percentage of victories constructed by combining the advantages of the methods to determine team standings used in Korean professional baseball. We also have applied preexistent methods and suggested method to past and present Korean professional baseball data.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.12
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• pp.565-572
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• 2017

Traditional method for time series analysis, autoregressive integrated moving average (ARIMA) allows to mine significant patterns from the past observations using autocorrelation and to forecast future sequences. However, Korean baseball games do not have regular intervals to analyze relationship among the past attendance observations. To address this issue, we propose artificial neural network (ANN) based attendance prediction model using various measures including performance, team characteristics and social influences. We optimized ANNs using grid search to construct optimal model for regression problem. The evaluation shows that the optimal and ensemble model outperform the baseline model, linear regression model.

• Asia Marketing Journal
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• v.25 no.3
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• pp.148-159
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• 2023

As Major League Baseball (MLB)'s continuous decline in popularity has caused its game attendance to drop gradually, the league makes a desperate attempt such as game rule changes to remain relevant. Along with the introduction of new rules to make games more dynamic such as the pitch clock, bigger bases, and defensive shift limitations, it is important for MLB franchises to understand drivers for game attendance. We focus on the effect of accumulated winning performance of the two teams on game attendance, one of the key drivers of game attendance, and investigate how it is influenced by consumer and industry factors such as online search and game rule changes. We find that game attendance increases as the prior winning performance of the home (away) team increases (decreases). We also find that online search and rule changes for more dynamic games moderate the effect of winning performance on game attendance.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.915-930
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• 2011

There are a variety of methods to model game results and many methods exist for the case of paired comparison data. Among them, the Bradley-Terry model is the most widely used to derive a latent preference scale from paired comparison data. It has been applied in a variety of fields in psychology and related disciplines. We applied this model to the data of Korean Baseball League. It shows that the loglinear Bradley-Terry model of defensive rate and save is optimal in terms of AIC. Also some categorical characteristics, such as east team and west team, existence of golden glove winning players, team(s) with seasonal pitching leader, and team(s) with home advantage, influenced the game result significantly. As a result, the suggested models can be further utilized to predict future game results.