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I am an Assistant Professor of Sport Analytics and of Statistics at Rice University. Much of my work involves what team front offices want to know: (a) how to measure individual contributions to team success in team sports and (b) how to squeeze optimal estimates of player talent from limited data. Building on these results, I research what league offices want to know: how teams and players respond to incentives, from a game theoretic perspective. I want to understand how leagues can design these incentives to promote the health of their sport. My favorite tools for these problems tend to come from statistical machine learning (regularized regression, gradient boosting, etc.) although I am also partial to Bayesian models when appropriate (and when the computational cost is reasonable). My favorite sports are baseball, soccer and volleyball.
I completed my PhD in statistics at Stanford University in 2017. From there, I worked for the Los Angeles Dodgers in R&D for five years and then spent one season as an Assistant General Manager with the Houston Astros before joining Rice in 2023. Along the way, I’ve kept a thread of consulting, starting with the Oakland Athletics, which led directly to part-time work for AZ Alkmaar, which became part-time work for Zelus Analytics (primarily soccer analytics), which became part-time work for Teamworks (soccer analytics).
Regretfully, I do not have the bandwidth to respond to individual requests from students for video calls or feedback on projects. If you are a potential collaborator with (a) data and (b) research questions, please reach out—I may be able to provide students and brainpower. I am also open to media inquiries.
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