  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.
