Date of this Version
Annals of Applied Statistics
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.
spatial models, Bayesian shrinkage, baseball fielding
Jensen, S. T., Shirley, K. E., & Wyner, A. J. (2009). Bayesball: A Bayesian Hierarchical Model for Evaluating Fielding in Major League Baseball. Annals of Applied Statistics, 3 (2), 491-520. http://dx.doi.org/10.1214/08-AOAS228
Date Posted: 27 November 2017
This document has been peer reviewed.