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New post! @timbryan000 uses text analysis to explore the NFL draft. There's a lot of really interesting/useful stuff here, including a dataset of scouting reports and analysis of linguistic variation. opensourcefootball.com/posts/2023-07-…
Using publicly available data and open-source code, I wrote (!) about constructing NFL draft curves and explained why top picks aren't as valuable as we think they are (if they aren't being used on a quarterback) On @Open_Source_FB: opensourcefootball.com/posts/2023-02-…
New post! @JonasTrostle examines defensive efficiency against WR1s relative to other receivers. Post: opensourcefootball.com/posts/2021-07-… Source code: github.com/nflverse/open-…
New post! @richjand demonstrates the use of multilevel modeling to estimate NFL team ability on offense and defense opensourcefootball.com/posts/2021-06-…
NEW for @Open_Source_FB: using 🔥🔥torch🔥🔥 for R to classify coverages using NFL player tracking data with a computer vision approach opensourcefootball.com/posts/2021-05-…
❗ New post for @Open_Source_FB: I wrote down everything I know about making an NFL win probability model using xgboost in R: opensourcefootball.com/posts/2021-04-…
New post! @bendominguez011 shows off how to use Python's sklearn to construct an NFL team strength model opensourcefootball.com/posts/2021-01-…
New post! @jacklich10 looks at penalties in the NFL. 2 big things stand out: --> Offenses have more control over penalties than defenses --> Some types of penalties carry more predictive power than others opensourcefootball.com/posts/2021-01-…
New post! @adrian_stats homefield advantage in the NFL over time, finding it to be greatly diminished in the most recent two seasons opensourcefootball.com/posts/2021-01-…
New post! @random_effects argues that more you look into the numbers, the better it looks for Aaron Rodgers opensourcefootball.com/posts/2020-10-…
New post! @awgymer uses the new roster functions in @nflfastR to look at trends in receiving by position over time opensourcefootball.com/posts/2020-09-…
New post! @richjand demonstrates the use of tidyModels to predict rush/pass decisions and looks at which teams have rushed or passed more than expected opensourcefootball.com/posts/2020-09-…
New post! @mikeyirene creates an Expected Field Goal metric, finding the all-powerful Justin Tucker No. 1 in field goals made above expected opensourcefootball.com/posts/2020-09-…
New post! @ThePuntRunts debuts an R package for puntalytics (!) and looks at punt return yardage allowed over expected opensourcefootball.com/posts/2020-08-…
New post! @reinhurdler takes a look at actual and expected fantasy points for receivers in 2019 using where players were targeted. And look at this gorgeous table! opensourcefootball.com/posts/2020-08-…
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