News

Where: TMCB 1170

When: April 10th @ 11am

Speaker: Will Melville

Game-Theoretically Optimal Strategies in Baseball

The purpose of our work is to define game-theoretically optimal strategies for every decision in a baseball game. We begin with a pitch sequencing model, which we use to define optimal swing decision strategies and pitch sequencing strategies. Next, we define a method to optimize fielder positioning against both static hitters who do not adapt their batted ball trajectories in response to the defense's positioning strategy and adaptable hitters who choose their batted ball trajectories in response to the defense's positioning strategy. Finally, we investigate managerial matchup decisions such as when to relieve a pitcher or pinch hit for a batter by modeling baseball as an extensive-form game. We define and evaluate five game playing algorithms, and we show that at least four of the algorithms could help actual baseball managers make winning decisions. 

William Melville received his undergraduate degree in applied and computational mathematics (ACME) at BYU in 2020 before starting a job as an analyst with the Texas Rangers. He returned to BYU in 2022, where he is currently pursuing a PhD in computer science. His research focuses on applications of game theory to baseball strategy.