If Markov played baseball

Speaker Name: Ryan Gantner (rgantner at sjfc dot edu )

Speaker Afiliation: St. John Fisher College

Abstract: There is a popular way of modeling the game of baseball using a probabilistic concept known as the Markov Chain. This model will be introduced and described in detail. Using actual recent Major League Baseball data, we'll build transition (and related) matrices and be able to do various analyses, such as the value of bunting, the value of base stealing, and the value of hitting home runs. We will talk about recent work which has been done regarding pitch calling and batting orders.

Target Audience: We'll use several concepts from linear algebra, including matrix multiplication, eigenvalues, and eigenvectors. Prior knowledge of these concepts will significantly help understanding. Some basic results of probability and Markov Chain theory will be discussed and used, though no prior knowledge will be assumed. The talk should be accessible to those with only a basic knowledge of how the game of baseball works.