The goal of this project is to use evaluation data collected on baseball athletes to make predictions about their on-field performance in competitive games. Evaluation data includes visual skills assessed with eye tracking, movement screening data and simulated batting performance metrics collected in virtual reality that are measured as part of the USA Baseball Prospect Development Pipeline. Using regression and Bayesian statistical analyses we will identify characteristics of these data that correlate with batting performance in order to inform scouts about the likely production of developmental prospects. The final product will be an application that uses an athlete's assessment results to produce performance summary graphs for the individual compared to other athletes and inferential models for the relationships between assessments and performance.
Project Leads: Marc Richard, Suhail Mithani, Greg Appelbaum