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Learning Bayesian Statistics

#91, Exploring European Football Analytics, with Max Göbel

64 min • 20 september 2023

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As you may know, I’m kind of a nerd. And I also love football — I've been a PSG fan since I’m 5 years old, so I’ve lived it all with this club.. And yet, I’ve never done a European-centered football analytics episode because, well, the US are much more advanced when it comes to sports analytics.

But today, I’m happy to say this day has come: a sports analytics episode where we can actually talk about European football. And that is thanks to Maximilan Göbel.

Max is a post-doctoral researcher in Economics and Finance at Bocconi University in Milan. Before that, he did his PhD in Economics at the Lisbon School of Economics and Management. 

Max is a very passionate football fan and played himself for almost 25 years in his local football club. Unfortunately, he had to give it up when starting his PhD — don’t worry, he still goes to the gym, or goes running and sometimes cycling.

Max is also a great cook, inspired by all kinds of Italian food, and an avid podcast listener — from financial news, to health and fitness content, and even a mysterious and entertaining Bayesian podcast…

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, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson, Stephen Oates, Gian Luca Di Tanna, Jack Wells, Matthew Maldonado, Ian Costley, Ally Salim, Larry Gill, Ian Moran, Paul Oreto, Colin Caprani, Colin Carroll, Nathaniel Burbank, Michael Osthege, Rémi Louf, Clive Edelsten, Henri Wallen, Hugo Botha, Vinh Nguyen, Raul Maldonado, Marcin Elantkowski, Adam C. Smith, Will Kurt, Andrew Moskowitz, Hector Munoz, Marco Gorelli, Simon Kessell, Bradley Rode, Patrick Kelley, Rick Anderson, Casper de Bruin, Philippe Labonde, Michael Hankin, Cameron Smith, Tomáš Frýda, Ryan Wesslen, Andreas Netti, Riley King, Yoshiyuki Hamajima, Sven De Maeyer, Michael DeCrescenzo, Fergal M, Mason Yahr, Naoya Kanai, Steven Rowland, Aubrey Clayton, Jeannine Sue, Omri Har Shemesh, Scott Anthony Robson, Robert Yolken, Or Duek, Pavel Dusek, Paul Cox, Trey Causey, Andreas Kröpelin, Raphaël R, Nicolas Rode, Gabriel Stechschulte, Arkady, Kurt TeKolste, Gergely Juhasz, Marcus Nölke, Maggi Mackintosh, Grant Pezzolesi, Avram Aelony, Joshua Meehl, Javier Sabio, Kristian Higgins, Alex Jones, Gregorio Aguilar, Matt Rosinski, Bart Trudeau and Luis Fonseca.

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

Links from the show:


Max's paper using Bayesian inference:


Forecasting Arctic Sea Ice:


Some of Max’s coauthors:


Abstract

by Christoph Bamberg

We already covered baseball analytics in the U.S.A. with Jim Albert in episode 85 and looked back at the decade long history of sports analytics there. How does it look like in Europe? 

To talk about this we got Max Göbel on the show. Max is a post-doctoral researcher in Economics and Finance at Bocconi University in Milan and holds a PhD in Economics from the Lisbon School of Economics and Management.

What qualifies him to talk about the sports-side of sports analytics is his passion for football and decades of playing experience. 

So, can sports analytics in Europe compete with analytics in the U.S.A.? Unfortunately, not yet. Many sports clubs do not use models in their hiring decisions, leading to suboptimal choices based on players’ reputation alone, as Max explains.

He designed a factor model for the performance of single players, borrowing from his econometrics expertise (check it out on his webpage, link in the show notes). 

We talk about how to grow this model from a simple and straight-forward Bernoulli model for the rate of scored goals to a multilevel model, incorporating other players. And of course, we discuss the benefits for using Bayesian statistics for this modelling problem.

We also cover sport analytics more generally and why it may not be so widely used in European football clubs yet. 

Besides his interest in football analytics, Max worked and works on topics in econometrics such as regression forecasting in the U.S.A., asset pricing and applying econometric methods to climate change issues like climate change forecasting and sea ice disappearance.

Transcript

This is an automatic transcript and may therefore contain errors. Please get in touch if you're willing to correct them.

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