Bayesball: A Bayesian hierarchical model for evaluating fielding in major league baseball
Abstract
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.
Cite
@article{arxiv.0802.4317,
title = {Bayesball: A Bayesian hierarchical model for evaluating fielding in major league baseball},
author = {Shane T. Jensen and Kenneth E. Shirley and Abraham J. Wyner},
journal= {arXiv preprint arXiv:0802.4317},
year = {2009}
}
Comments
Published in at http://dx.doi.org/10.1214/08-AOAS228 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)