#25 Bayesian Stats in Football Analytics, with Kevin Minkus
Learning Bayesian Statistics - Podcast autorstwa Alexandre Andorra
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Have you watched the series « The English Game », on Netflix? Well, I think you should — it’s a fascinating dive into how football went from an aristocratic to a popular sport in the late 19th century England. Today it is so popular that it became a valuable business to do statistics on the game and its players!
To talk about that, I invited Kevin Minkus on the show — he’s a data scientist and soccer fan living in Philadelphia. Kevin’s currently working at Monetate on ecommerce problems, and prior to Monetate he worked on property and casualty insurance pricing.
He spends a lot of his spare time working on problems in football analytics and is a contributor at American Soccer Analysis, a website and podcast dedicated to… football made or played in the US (or “soccer”, as they say over there). Kevin is responsible for some of their data management and devops, and he recently wrote a guide to football analytics for the Major League Soccer’s website, entitled « Soccer Analytics 101 ».
To be honest, I had a great time talking for one hour about two of my passions — football and stats! Soooo, maybe 2020 isn’t that bad after all… Ow, and beyond football, Kevin is also into the digital humanities, web development, 3D animation, machine learning, and… the bassoon!
Our theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work at https://bababrinkman.com/ !
Links from the show:
- Kevin on Twitter: https://twitter.com/kevinminkus
- Kevin on GitHub: https://github.com/kcm30
- Soccer Analytics 101: https://www.mlssoccer.com/soccer-analytics-guide/2020/soccer-analytics-101
- American Soccer Analysis: https://www.americansocceranalysis.com/
