We discuss a previous Big Data Bowl finalist paper `Expected Hypothetical Completion Probability` (https://arxiv.org/abs/1910.12337) with authors Sameer Deshpande (@skdeshpande91) and Kathy Evans (@CausalKathy). 

Sameer is a postdoctoral associate at MIT. Prior to that, he completed his Ph.D. at the Wharton School of the University of Pennsylvania. He is broadly interested in Bayesian methods and causal inference. He is a long-suffering but unapologetic fan of America's Team. He's also a fan of the Dallas Mavericks.

Kathy is the Director of Strategic Research for the Toronto Raptors. She completed her Ph.D. in Biostatistics at Harvard University. She doesn't have an opinion on Frequentist vs Bayesian or R vs Python, but will get very upset if Rise of Skywalker is your favorite Star Wars movie.

For additional references mentioned in the show:

• Big Data Bowl notebooks: https://www.kaggle.com/c/nfl-big-data-bowl-2021/notebooks


• BART: https://arxiv.org/abs/0806.3286


• XBART: Accelerated Bayesian Additive Regression Trees https://jingyuhe.com/xbart.html


• Matthew Reyers (@Stats_By_Matt) thesis: https://twitter.com/Stats_By_Matt/status/1296570171687989249?s=20 

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