Ron Yurko, Assistant Teaching Professor and Director of the Carnegie Mellon Sports Analytics Center, Department of Statistics & Data Science, Carnegie Mellon University

Title: If you change it, will they call it? Estimating the causal effect of rule changes on the variability of umpire strike zones

Abstract: In recent seasons, Major League Baseball (MLB) has introduced notable changes to strike zone officiating. In 2025, MLB changed the buffer used to evaluate umpires from two inches outside the strike zone to three-quarters of an inch on each side of the strike zone. Then in 2026, MLB introduced the Automated Ball-Strike (ABS) challenge system, enabling players to challenge the umpire's call. Evaluating how these rule changes alter umpire behavior requires separating the effect of the rule changes from any underlying temporal confounding in umpire aging and trajectory dynamics. In this work, we fit Bayesian Additive Regression Tree (BART) and Gaussian Process (GP) models to capture the spatial and temporal variation in each umpire's called strike probabilities between 2009 and 2024. We then use these models to forecast each umpire's counterfactual called strike probabilities that would be observed had the new buffer and ABS systems not been implemented. Our modeling allows us to evaluate whether MLB's rule changes have reduced umpire-to-umpire variability and produced more homogeneous called-strike behavior. This study illustrates the challenging nuances of causal inference, resulting in a framework for evaluating rule changes when nonlinear spatial dynamics and longitudinal confounding throw a curveball at modern sports analytics. This is based on joint work with Sameer Deshpande and Jared Fisher.

Ron Yurko is an Assistant Teaching Professor in the Department of Statistics & Data Science at Carnegie Mellon University and the Director of the Carnegie Mellon Sports Analytics Center (CMSAC). His research focuses on developing statistical methods at the interface of inference and machine learning, with applications in sports analytics and natural language processing. Under his leadership, CMSAC drives high-impact industry partnerships, including recent collaborations with the NFL Draft and the Heisman Hopefuls platform. His work and commentary have been featured in major outlets such as The Athletic, ESPN, CBS, and NBC. He has industry experience in finance and professional sports, and holds bachelor's, master's, and PhD degrees in Statistics from Carnegie Mellon.

Second Keynote Speaker: To be announced

Title: To be announced

Abstract and biography forthcoming.