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

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

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.

Related Works:

Keywords: Spatial models; Bayesian shrinkage; baseball fielding

Full-text: Access denied (no subscription detected)

In 2007, access to the Annals of Applied Statistics was open. Beginning in 2008, you must hold a subscription or be a member of the IMS to view the full journal. For more information on subscribing, please visit: http://imstat.org/orders.
If you are already an IMS member, you may need to update your Euclid profile following the instructions here: http://imstat.org/publications/eaccess.htm.
Links and Identifiers

Permanent link to this document: http://projecteuclid.org/euclid.aoas/1245676183
Digital Object Identifier: doi:10.1214/08-AOAS228
Zentralblatt MATH identifier: 1166.62385

References

Albert, J. H. and Chib, S. (1993). Bayesian analysis of binary and polychotomous response data., J. Amer. Statist. Assoc. 88 669–679.
Mathematical Reviews (MathSciNet): MR1224394
Zentralblatt MATH: 0774.62031
Digital Object Identifier: doi:10.2307/2290350
BIS (2007). Baseball info solutions. Available at, www.baseballinfosolutions.com.
Dewan, J. (2006)., The Fielding Bible. ACTA Sports, Skokie, IL.
Gelman, A. (2006). Prior distributions for variance parameters in hierarchical models., Bayesian Anal. 1 515–533.
Mathematical Reviews (MathSciNet): MR2221284
Digital Object Identifier: doi:10.1214/06-BA117A
Gelman, A., Carlin, J., Stern, H. and Rubin, D. (2003)., Bayesian Data Analysis, 2nd ed. Chapman & Hall, Boca Raton, FL.
Mathematical Reviews (MathSciNet): MR1385925
Geman, S. and Geman, D. (1984). Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images., IEEE Transaction on Pattern Analysis and Machine Intelligence 6 721–741.
Glickman, M. E. and Stern, H. S. (1998). A state-space model for national football league scores., J. Amer. Statist. Assoc. 93 25–35.
Jensen, S. T., Shirley, K. and Wyner, A. J. (2009). Supplement to “Bayesball: A Bayesian hierarchical model for evaluating fielding in major league baseball.” DOI:, 10.1214/08-AOAS228SUPP.
Kalist, D. E. and Spurr, S. J. (2006). Baseball errors., Journal of Quantitative Analysis in Sports 2 Article 3.
Mathematical Reviews (MathSciNet): MR2270282
Digital Object Identifier: doi:10.2202/1559-0410.1043
Lichtman, M. (2003). Ultimate zone rating. The Baseball Think Factory, March 14,, 2003.
Pinto, D. (2006). Probabilistic models of range. Baseball Musings, December 11,, 2006.
Reich, B. J., Hodges, J. S., Carlin, B. P. and Reich, A. M. (2006). A spatial analysis of basketball shot chart data., Amer. Statist. 60 3–12.
Thorn, J. and Palmer, P. (1993)., Total Baseball. Harper Collins, New York.

2009 © Institute of Mathematical Statistics