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#108 Modeling Sports & Extracting Player Values, with Paul Sabin image

#108 Modeling Sports & Extracting Player Values, with Paul Sabin

S1 E108 · Learning Bayesian Statistics
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Folks, you may know it by now: I’m a huge sports fan! So needless to say that this episode was like being in a candy store for me. Paul Sabin is so knowledgeable that this conversation was an absolute blast for me!

In it, Paul discusses his experience with non-stats stakeholders in sports analytics and the challenges of convincing them to adopt evidence-based decisions. He also explains his soccer power ratings and projections model, which uses a Bayesian approach and expected goals, as well as the importance of understanding player value in difficult-to-measure positions, and the need for more accessible and digestible sports analytics for fans. 

We also touch on the impact of budget on team performance in American sports and the use of plus-minus models in basketball and American football.

Paul is a Senior Fellow at The Wharton Sports Analytics & Business Initiative and a Lecturer in the Department of Statistics and Data Science at The Wharton School of The University of Pennsylvania. He has spent his entire career as a sports analytics professional, teaching and leading sports analytics research projects.

Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !

Thank you to my Patrons for making this episode possible!

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