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
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)
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
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
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)
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
AFC North
Passing Leaders:
aDOT - Jackson
% > 15AY - Jackson
EPA / Pass - Jackson
Data via @nflscrapR
(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
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