Bayesball: A Bayesian hierarchical model for evaluating fielding in major league baseball

Details Bayesball: A Bayesian hierarchical model for evaluating fielding in major league baseball Bayesball: A Bayesian hierarchical model for evaluating fielding in major league baseball

2008-02-29

arxiv.org/abs/0802.4317v3

Annals of Applied Statistics 2009, Vol. 3, No. 2, 491-520

Statistics

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Published in at http://dx.doi.org/10.1214/08-AOAS228 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Ins

Scientific paper

10.1214/08-AOAS228

The use of statistical modeling in baseball has received substantial attention recently in both the media and academic community. We focus on a relatively under-explored topic: the use of statistical models for the analysis of fielding based on high-resolution data consisting of on-field location of batted balls. We combine spatial modeling with a hierarchical Bayesian structure in order to evaluate the performance of individual fielders while sharing information between fielders at each position. We present results across four seasons of MLB data (2002--2005) and compare our approach to other fielding evaluation procedures.

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