Predicting Batting Averages in Major League Baseball

DOI: 10.5176/2251-1938_ORS18.16

Authors: Sarah R. Bailey and Tim B. Swartz

Abstract:

This paper considers the use of ball-by-ball data provided by the Statcast system in the prediction of batting averages for Major League Baseball. The publicly available Statcast data and resultant predictions supplement proprietary PECOTA forecasts. The rationale behind the use of the detailed Statcast data is the discovery of a luck component to batting. It is anticipated that luck component will not be repeated in future seasons. The two predictions (Statcast and PECOTA) are combined via simple linear regression to provide improved forecasts of batting average.

Keywords: Big data, Forecasting, Logistic regression, PECOTA, Statcast.