#49 The Present & Future of Baseball Analytics, with Ehsan Bokhari

Learning Bayesian Statistics

It’s been a while since I did an episode about sports analytics, right? And you know it’s a field I love, so… let’s do that!

For this episode, I was happy to host Ehsan Bokhari, not only because he’s a first-hour listener of the podcast and spread the word about it whenever he can, but mainly because he knows baseball analytics very well!

Currently Senior Director of Strategic Decision Making with the Houston Astros, he previously worked there as Senior Director of Player Evaluation and Director of R&D. And before that, he was Senior Director at the Los Angeles Dodgers from the 2015 to the 2018 season.

Among other things, we talked about what his job looks like, how Bayesian the field is, which pushbacks he gets, and what the future of baseball analytics look like to him.

Ehsan also has an interesting background, coming from both psychology and mathematics. Indeed, he received a PhD in quantitative psychology and an MS in statistics at the University of Illinois in 2014.

Maybe most importantly, he loves reading non-fiction and spending time with his almost three-year-old son — who he read Bayesian Probability for Babies to, of course.

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!

Yusuke Saito, Avi Bryant, Ero Carrera, Brian Huey, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, Adam Bartonicek, William Benton, Alan O'Donnell, Mark Ormsby, Demetri Pananos, James Ahloy, Jon Berezowski, Robin Taylor, Thomas Wiecki, Chad Scherrer, Nathaniel Neitzke, Zwelithini Tunyiswa, Elea McDonnell Feit, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Joshua Duncan, Ian Moran, Paul Oreto, Colin Caprani, George Ho, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Tim Radtke, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Matthew McAnear, Michael Hankin, Cameron Smith, Luis Iberico, and Alejandro Morales.

Visit https://www.patreon.com/learnbayesstats to unlock exclusive Bayesian swag ;)

Links from the show:

• Ehsan on LinkedIn: https://www.linkedin.com/in/ebokhari/
• Bayesian Bagging to Generate Uncertainty Intervals -- A Catcher Framing Story: https://www.baseballprospectus.com/news/article/38289/bayesian-bagging-generate-uncertainty-intervals-catcher-framing-story/
• Jim Albert's Bayesball blog: https://bayesball.github.io/
• Simulation of empirical Bayesian methods, using baseball statistics: http://varianceexplained.org/r/simulation-bayes-baseball/
• Detection and Characterization of Cluster Substructure -- Fuzzy c-Lines: https://epubs.siam.org/doi/abs/10.1137/0140029
• Tensor rank decomposition: https://en.wikipedia.org/wiki/Tensor_rank_decomposition
• Statistical Prediction versus Clinical Prediction -- Improving What Works: https://meehl.umn.edu/sites/meehl.umn.edu/files/files/155dfm1993.pdf
• Clinical Versus Actuarial Judgment: https://meehl.umn.edu/sites/meehl.umn.edu/files/files/138cstixdawesfaustmeehl.pdf
• Clinical Versus Statistical Prediction: https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.693.6031&rep=rep1&type=pdf