This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 520
Type: Contributed
Date/Time: Wednesday, August 4, 2010 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #308989
Title: Building Time Series Into Hierarchical Bayesian Models with Applications in Baseball Fielding
Author(s): James Martin Piette*+ and Shane Jensen
Companies: The Wharton School, University of Pennsylvania and The Wharton School, University of Pennsylvania
Address: 400 Jon M. Huntsman Hall, Philadelphia, PA, 19104-6340,
Keywords: Bayesian shrinkage ; baseball fielding ; spatial models ; time series
Abstract:

It has become common for people around baseball to involve statistical analysis in their personnel decisions, which requires an understanding of a player's ability to field. While well-researched, the question behind how best to model fielding ability is prodigiously debated amongst experts. Jensen et al took a rigorous statistical approach to the problem by implementing a hierarchical Bayesian structure in a spatial model setting. Using this approach, they can gauge the performance of individual fielders with more accuracy due to the additional information provided via sharing across fielders. We aim to take this model one step further by building a time series aspect into this previous model. This allows for an estimation of a player's underlying fielding ability, aggregated across all seasons, and provide a look at time trends in the abilities of an average Major League fielder.


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