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ISBA BERaP Webinar (5/13) - Teaching Bayesian Methods in Modern Sports Analytics

  • 1.  ISBA BERaP Webinar (5/13) - Teaching Bayesian Methods in Modern Sports Analytics

    Posted an hour ago

    Dear ASA Community,

     

    As the Bayesian Education Research and Practice (BERaP) section of the International Society for Bayesian Analysis (ISBA), we invite you to attend the following webinar about Teaching Bayesian Methods in Modern Sports Analytics. If you have any questions, please reach out to Becky Tang at btang@middlebury.edu, or visit the BERaP website https://berap-isba.github.io/ where you can find a list of updates, future events, and recordings of past webinars. 

     

    Title: Teaching Bayesian Methods in Modern Sports Analytics

    Presenter(s): Ron Yurko (Carnegie Mellon)

    Date and Time: May 13th, 12 pm ET

    Registration link: https://us06web.zoom.us/webinar/register/WN_cM9P6xK6T-OgOaxrCjKJtA#/registration 

     

    Description: Since the release of Moneyball, the field of sports analytics has grown from a niche interest into a technically mature field. In this webinar, I will first discuss why common problems and challenges in modern sports analytics research, e.g., player/team evaluation and communicating uncertainty, warrants Bayesian thinking. Then, I will provide an overview of a course offered at Carnegie Mellon that introduces advanced undergraduates and graduate students to applied Bayesian modeling through sports analytics. Using real problems faced by professional sports teams, I will share strategies for teaching core Bayesian concepts, such as constructing priors, building hierarchical models, and simulating with the posterior predictive distribution. Finally, I will highlight accessible sports analytics resources and datasets that instructors can use to integrate Bayesian thinking into their own curriculum.

     

    Best,

    Shaoyang Ning

     

    On behalf of ISBA-BERaP section

    Becky Tang

    Vanda Inacio

    Shaoyang Ning

    Michael Pearce





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    Shaoyang Ning
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