Welcome
110h issue.
Good hodgepodge of links this week, albeit mainly focused on football, both NFL and college. The one outlier is an MLB article taking a look at who might win the postseason awards.
I am interested in sports-related data science opportunities within the betting or DFS space. Know someone I should chat with? I'll buy you a coffee.
Self Promotion
I recently created SP K Prediction, which identifies positive expected value in MLB starting pitcher strikeout bets and automatically updates each morning. Additionally, it creates market odds for which pitcher will have the most strikeouts that day based on 10k simulations. Check it out, I think it's rad.
This Week's Lineup
Introduction to NFL Analytics with R
What better way to learn NFL Analytics than with this extensive documentation with R.
I analyzed 850,000 ESPN In-Game Win Probabilities.
A professional options trader and avid CFB fan investigated how good the accuracy of the ESPN live win probability model is.
MLB Award Predictions
What does the data reveal about who should come out on top in baseball's top honors? We’re breaking them down in our MLB award predictions.
Success Rate Comes to Pro Football Reference
They define it as a play that gains at least 40% of yards required on 1st down, 60% of yards required on 2nd down, and 100% on 3rd or 4th down.
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Unexpected Points Added is curated and maintained by Patrick Hayes.
I have completed a Master of Applied Data Science from the University of Michigan; let's connect.
Send me an email with your feedback or questions. I respond to every single one.