Project Description:

Baseball has a well-established accounting system for batted balls in singles, doubles, triples, and homeruns that is wonderfully easy to see and intuitive. However, while reasonable at the box score level and casual fan level, this accounting system doesn’t maximize predictability in a year-to-year context. In the context of the immense value of accurately projecting future performance, is it possible to design an accounting system that groups batted balls in a predictive manner? In an analytical sense, can we group batted balls into clusters and assign a weight to the frequency of batted balls in each category as a means for projecting a given batter’s future weighted on-base average (wOBA)?

Project Photo:

Student Team Members

• Tad Berkery
• Justin Nam

Course Faculty

Project Mentors, Sponsors, and Partners

• Anton Dahbura
• Sig Mejdal