I've been developing my probabilistic modeling capabilities this year at work, so in my free time I thought it'd be a fun exercise to write an article about modeling MLB win probabilities using a Bayesian Hierarchical model with Stan. If this interests you, then give it a whirl! If not, then just pretend to read it and tell me I did great!! https://lnkd.in/gbwvJDxw #Stan #BayesianStatistics
Alexandra M.
2mo
interesting stuff! i'd love to connect. hope all has been well.
Tom English
2mo
Hey Derek you did great!!! Maybe I'll read later.
Andrew Oates
2mo
Interesting data Derek! Slightly consoling to read after the Brewers wildcard loss last week.
Rosalio Bueno
2mo
Interesting. Gob job considering various algorithms!
Hello. I do not know you but I can tell you’re extremely intelligent/educated. However, the problem with analytics in the game of baseball is that they do not measure “anything” that truly matters. I am very analytical and understand that “numbers don’t lie.” However, they do not measure what makes a hitter, pitcher, fielder, coach etc a winner, productive athlete, successful, etc. If you or anyone that reads this would like to understand more of what I’m talking about…..feel free to reach out. I would absolutely have no problem learning from you as long as you’re willing to listen to what I know, have lived, learned, and “done.” I also somewhat understand high level math too. Appreciate the post 👊🏼
Data Analytics | Data Comedian | Director @ PyMC Labs
2moWow, great post! Especially since it confirms my prior that the Braves were terribly unlucky. I do think the sequencing of hits makes a huge difference. Perhaps even just accounting for variability of hard-hit% across the order would be helpful. When team has high variability, then there are a few players hitting much better, making it harder to sequence hits or hit with runners on? Just a thought.