Open Source Football

Tweets by @benbbaldwin and @mrcaseb

[Open Source Football @Open_Source_FB]

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.

https://t.co/xmnEZJih3M

[Computer Cowboy @benbbaldwin]

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: https://t.co/1VmBLgowbr

[Open Source Football @Open_Source_FB]

@EthanCDouglas @nflfastR ,,,

[Open Source Football @Open_Source_FB]

New post!

@JonasTrostle examines defensive efficiency against WR1s relative to other receivers.

Post: https://t.co/wDfGHoWCOS

Source code: https://t.co/6dBN8ni1kV

[Open Source Football @Open_Source_FB]

New post! @richjand demonstrates the use of multilevel modeling to estimate NFL team ability on offense and defense

https://t.co/IBWvD6XJOO

[Computer Cowboy @benbbaldwin]

NEW for @Open_Source_FB: using 🔥🔥torch🔥🔥 for R to classify coverages using NFL player tracking data with a computer vision approach

https://t.co/ufqeC2DUe7

[Computer Cowboy @benbbaldwin]

❗ New post for @Open_Source_FB: I wrote down everything I know about making an NFL win probability model using xgboost in R:

https://t.co/dYEF2CQXml

[Open Source Football @Open_Source_FB]

New post from @Danderso13!

[Open Source Football @Open_Source_FB]

New post! @bendominguez011 shows off how to use Python's sklearn to construct an NFL team strength model

https://t.co/uTojSxpFrb

[Open Source Football @Open_Source_FB]

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

https://t.co/jRumVzlbZG

[Open Source Football @Open_Source_FB]

New post!

@adrian_stats homefield advantage in the NFL over time, finding it to be greatly diminished in the most recent two seasons

https://t.co/LRPVoc4noK

[Open Source Football @Open_Source_FB]

@jacklich10 Source code here: https://t.co/EwE6s2fka3

[Open Source Football @Open_Source_FB]

New post! From @jacklich10

Exploring best ways to factor in opponents when opponent-adjusting EPA

This figure here shows how the team tiers chart changes when taking opponents into account

https://t.co/EkZUu2oCHy

[Open Source Football @Open_Source_FB]

New post!

@random_effects argues that more you look into the numbers, the better it looks for Aaron Rodgers

https://t.co/P9gQWVBflB

[Open Source Football @Open_Source_FB]

New post!

@awgymer uses the new roster functions in @nflfastR to look at trends in receiving by position over time

https://t.co/lo12CebWcq

[Open Source Football @Open_Source_FB]

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

https://t.co/pJb2gFmNtB

[Open Source Football @Open_Source_FB]

New post!

@mikeyirene creates an Expected Field Goal metric, finding the all-powerful Justin Tucker No. 1 in field goals made above expected

https://t.co/n4PAZ9shEK

[Open Source Football @Open_Source_FB]

New post!

@ThePuntRunts debuts an R package for puntalytics (!) and looks at punt return yardage allowed over expected

https://t.co/2ShyvkYzdv

[Open Source Football @Open_Source_FB]

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!

https://t.co/Tj97vE2m9r