Potential Project Description for 2012-13


Title: Analyzing Baseball Strategy
Domain Expert: Matt Richey (Mathematics, Statistics, and Computer Science)

Recently, a great deal of thought has gone into developing new statistics for analyzing player performance. Less thought has go into developing methods for analyzing baseball strategy. For example, what effect does lineup order have on total runs? When is bunting a good idea. Is it better to have a more high "on base" players or more "slugging" hitters?

One way to approach this problem is through simulation, specifically stochastic simulation. In this project, I want to build a computer simulation that represents a probabilistic path through a base game. This is much like von Neumann's original approach to estimations of neutron scattering at Los Alamos. Instead of trying to analytically determine the values of certain parameters (e.g., average runs scored), the aim is to estimate these parameters via simulation. The key in this simulation will be to develop Markov chain transition matrices for each major league batter and then use these matrices to drive the simulation. The goal is to build a system in which every major league team is represented, arbitrary line ups of players can be selected, strategies implemented, etc. The simulator should be capable of running millions of games in order to accurately estimate the parameters in question.

Background in probability, statistics, and/or computation (particularly in a compiled high level language such as C++) is preferred.