Estimating fielding ability in baseball players over time

It is commonplace around baseball to involve statistical analysis in the evaluation of a player\u27s ability to field. While well-researched, the question behind how best to model fielding is heavily debated. The official MLB method for tracking fielding is riddled with biases and censoring problems, while more recent approaches to fielding evaluation, such as Ultimate Zone Rating [Lichtman 2003], lose accuracy by not treating the field as a single continuous surface. SAFE, Spatial Aggregate Fielding Evaluation, aims to solve these problems. Jensen et al [2009] took a rigorous statistical approach to this problem by implementing a hierarchical Bayesian structure in a spatial model setting. The performance of individual fielders can be more accurately gauged because of the additional information provided via sharing across fielders. I have extended this model to three new specifications by building in time series aspects: the constant-over-time model, the moving average age model and the autoregressive age model. By using these new models, I have produced a more accurate estimation of a players seasonal fielding performance and added insight into the aging process of a baseball player\u27s underlying ability to field