Journal of Quantitative Analysis in Sports
An official journal of the American Statistical Association
Editor-in-Chief: Glickman, PhD, Mark
SCImago Journal Rank (SJR) 2014: 0.265
Source Normalized Impact per Paper (SNIP) 2014: 0.513
Impact per Publication (IPP) 2014: 0.452
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Most Downloaded Articles
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- A generative model for predicting outcomes in college basketball by Ruiz, Francisco J. R. and Perez-Cruz, Fernando
- Building an NCAA men’s basketball predictive model and quantifying its success by Lopez, Michael J. and Matthews, Gregory J.
- openWAR: An open source system for evaluating overall player performance in major league baseball by Baumer, Benjamin S./ Jensen, Shane T. and Matthews, Gregory J.
Estimating Fielding Ability in Baseball Players Over Time
1University of Pennsylvania
2University of Pennsylvania
Citation Information: Journal of Quantitative Analysis in Sports. Volume 8, Issue 3, ISSN (Online) 1559-0410, DOI: 10.1515/1559-0410.1463, October 2012
- Published Online:
Quantitative evaluation of fielding ability in baseball has been an ongoing challenge for statisticians. Detailed recording of ball-in-play data in recent years has spurred the development of sophisticated fielding models. Foremost among these approaches, Jensen et al. (2009) used a hierarchical Bayesian model to estimate spatial fielding curves for individual players. These previous efforts have not addressed evolution in a player’s fielding ability over time. We expand the work of Jensen et al. (2009) to model the fielding ability of individual players over multiple seasons. Several different models are implemented and compared via posterior predictive validation on hold-out data. Among our choices, we find that a model which imposes shrinkage towards an age-specific average gives the best performance. Our temporal models allow us to delineate the performance of a fielder on a season-to-season basis versus their entire career.