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Batting index prediction model 2017
Journal of the Korean Data & Information Science Society 2017;28:635-45
Published online May 31, 2017
© 2017 Korean Data & Information Science Society.

Chong Sun Hong1 · Dong Sik Shin2

12Department of Statistics, Sungkyunkwan University
Correspondence to: Chong Sun Hong
Professor, Department of Statistics, Sungkyunkwan University, Seoul 03063, Korea. E-mail: cshong@skku.edu
Received April 3, 2017; Revised May 8, 2017; Accepted May 15, 2017.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
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.
Keywords : Batting, index, longitudinal study, pitching, weighted mean.


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