Bayesball: A Bayesian Hierarchical Model for Evaluating Fielding in Major League Baseball

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...

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Bibliographic Details
Published in:The annals of applied statistics 2009-06, Vol.3 (2), p.491-520
Main Authors: Jensen, Shane T., Shirley, Kenneth E., Wyner, Abraham J.
Format: Article
Language:English
Subjects:
Angular velocity
Arithmetic mean
Baseball
baseball fielding
Baseball statistics
Bayesian shrinkage
Coefficients
Combinatorics. Ordered structures
Contour lines
Coordinate systems
Cost estimation models
Density estimation
Exact sciences and technology
Mathematics
Modeling
Order, lattices, ordered algebraic structures
Sciences and techniques of general use
Spatial models
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Summary: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.
ISSN:1932-6157
1941-7330
DOI:10.1214/08-AOAS228