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Pound the Rock Football Analytics | Columbia Sports Management Grad Student

New York, NY
Joined January 2019
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PTR Football Analytics retweeted
(1/2) At BLA, we're hiring (paid) data science + engineering interns to work on sports betting models. Apply below! Past interns such as @CharlieGel @JakeFlancer @peterxeno have: - Processed sports data - Built models to project players - Built apps to evaluate predictions
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Have a favorite prospect? Curious if he'll be available when your team picks? Created a basic survival model to estimate this. Uses consensus rank, position, and pos rank. W/o team needs, it's a BPA approach For other top 100 prospects: tinyurl.com/y9klqsot (Tableau Pub)
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Of course, a huge thanks is due to @ArifHasanNFL for making his big boards public over the years Also, H/T to @SethWalder, whose responses to inquiries about ESPN's model were a helpful sanity check for my work Lastly, @bburkeESPN's past work on AFA was also incredibly helpful
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Will also try to live update throughout the draft tonight. The dashboard might be too much to keep updated, but can hopefully make simpler charts for specific prospects. Feel free to ask if I can pull up a specific prospect as the night goes on!
Quick one. Looked at field goal percent over expectation. Adjusting for kick difficulty, @JoshLambo managed to separate himself from the field and the 🐐 No pro bowl invite? The disrespect... Data via @nflscrapR
Question for the panel. What’s the lowest hanging fruit that most NFL teams still need to apply analytics to? In-game decision making? Player evaluation? Salary cap strategy? #MoveTheChains #SSAC20
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Mike Leach + Mina Kimes is everything
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Awesome #SSAC20 workshop for anyone wanting to get an intro to NFL tracking data from two NFL (@Jaguars) analytics personnel I’ll see you all there👍🏻
Hi Sports Analytics Twitter! Momin Ghaffar and I will be co-leading a #SSAC20 workshop, Intro to NFL Player Tracking Data in R, on Saturday from 12:15-1:15 PM (Room 205A)! Big shoutout to @StatsbyLopez for his help making this workshop a reality! (1/5)
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Opponent’s territory punt
Write a sad football story in 3 words
Premise: Passes over 15 air yards show highest EPA per PA New Finding: % of passes >= 15 air yards better explains QB EPA per PA than aDOT Division charts first. Proof of concepts later NFC West Passing Leaders: aDOT - LET % > 15AY - RUSS EPA / Pass - COOK Data via @nflscrapR
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AFC North Passing Leaders: aDOT - Jackson % > 15AY - Jackson EPA / Pass - Jackson Data via @nflscrapR
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Proof of concepts. 1) EPA per PA around max at 15 air yards and beyond 2&3) % >= 15 AY better explains EPA / Play than aDOT (r^2 of .26 vs .17) Limitations: Longer passes take longer to develop. This analysis does not take into account sacks or throwaways
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This account is now officially a NY Guardians account. XFL analytics coming soon🤷🏻‍♂️
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(1/n) Created a basic NFL Leverage Index (LI). Predicts the magnitude of a play's shift in WP based on pre-snap game state Most top LI plays featured the team w/ the ball down one possession, in opponent's red zone, with < 60sec left Data - @nflscrapR teapawt.net/i/status/1206372172232…
NO DOUBT ABOUT THAT ONE! TOUCHDOWN JULIO!
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Probably should put this intro in simpler language... A leverage index predicts how influential a play is likely to be to the final outcome of the game. A LI of 1 is average Julio’s game winning catch features in video had a pre-snap LI of 9+
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