Browse > Article
http://dx.doi.org/10.5351/KJAS.2013.26.4.649

Analysis of the Korean Baseball League using a Markov Chain Model  

Moon, Hyung Woo (Department of Computer Engineering, Changwon National University)
Woo, Yong Tae (Department of Computer Engineering, Changwon National University)
Shin, Yang Woo (Department of Statistics, Changwon National University)
Publication Information
The Korean Journal of Applied Statistics / v.26, no.4, 2013 , pp. 649-659 More about this Journal
Abstract
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.
Keywords
Baseball; distribution of the number of runs scored; distribution of the number of batters; Markov chain;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 Lee, J. T. and Cho, H. S. (2009). Win-loss models when two teams meet using data mining in the Korean pro-baseball, Journal of the Korean Data Analysis Society, 11, 3417-3426.
2 Shin, Y. W. (2011). Introduction to Stochastic Processes, Kyungmoon Publishers, Seoul.
3 Sokol, J. S. (2003). A robust heuristic for batting order optimization under uncertainty, Journal of Heuristics, 9, 353-370.   DOI
4 Tesar, N. Estimating expected runs using a Markov model for baseball, https://www.edsolio.com/media/2/265/files/TesarFinal_Draft.pdf.
5 Bae, J. Y., Lee, J. M. and Lee, J. Y. (2012). Predicting Korea Pro-baseball rankings by principal component regression analysis, Communications of the Korean Statistical Society, 19, 367-379.   과학기술학회마을   DOI   ScienceOn
6 Bukiet, B., Harold, E. R. and Palacios, J. L. (1997). A Markov chain approach to baseball, Operations Research, 45, 14-23.   DOI   ScienceOn
7 Cho, Y. S., Cho, Y. J. and Shin, S. G. (2007). A study on winning and losing in Korean professional baseball league, Journal of the Korean Data Analysis Society, 9, 501-510.
8 Choi, Y. G. and Kim, H. M. (2011). A statistical study on Korean baseball league games, The Korean Journal of Applied Statistics, 24, 915-930.   과학기술학회마을   DOI   ScienceOn
9 Hirotsu, N. and Wright, M. (2003). A Markov chain approach to optimal pinch hitting strategies in a designated hitter rule baseball game, Journal of the Operations Research Society of Japan, 46, 353-371.   DOI
10 D'Esopo, D. A. and Lefkowitz, B. (1960). The distribution of runs in the game of baseball, SRI Internal report.
11 Hirotsu, N. and Wright, M. (2005). Modelling a baseball game to optimise pitcher substitution strategies incorporating handedness of players, IMA Journal of Management Mathematics, 16, 179-194.   DOI   ScienceOn
12 Kim, H. (2011). Suggestion of a new method of computing percentage of victories for the Korean professional baseball, The Korean Journal of Applied Statistics, 6, 1139-1148.   과학기술학회마을   DOI   ScienceOn