The Annals of Applied Statistics

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

Shane T. Jensen, Kenneth E. Shirley, and Abraham J. Wyner

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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.

Article information

Source
Ann. Appl. Stat., Volume 3, Number 2 (2009), 491-520.

Dates
First available in Project Euclid: 22 June 2009

Permanent link to this document
https://projecteuclid.org/euclid.aoas/1245676183

Digital Object Identifier
doi:10.1214/08-AOAS228

Mathematical Reviews number (MathSciNet)
MR2750670

Zentralblatt MATH identifier
1166.62385

Keywords
Spatial models Bayesian shrinkage baseball fielding

Citation

Jensen, Shane T.; Shirley, Kenneth E.; Wyner, Abraham J. Bayesball: A Bayesian hierarchical model for evaluating fielding in major league baseball. Ann. Appl. Stat. 3 (2009), no. 2, 491--520. doi:10.1214/08-AOAS228. https://projecteuclid.org/euclid.aoas/1245676183


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