README.md
In mrcaseb/pages_dummy: Functions to Efficiently Scrape NFL Play by Play Data

nflfastR

GitHub release (latest by
date)

nflfastR is a set of functions to efficiently scrape NFL play-by-play data. nflfastR expands upon the features of nflscrapR:

The package contains NFL play-by-play data back to 1999
As suggested by the package name, it obtains games much faster
Includes completion probability (cp) and completion percentage over expected (cpoe) in play-by-play going back to 2006
Includes drive information, including drive starting position and drive result
Includes series information, including series number and series success
Hosts a repository of play-by-play data going back to 1999 for very quick access
Features new and enhanced models for Expected Points, Win Probability, and Completion Probability (see section below)

We owe a debt of gratitude to the original nflscrapR team, Maksim Horowitz, Ronald Yurko, and Samuel Ventura, without whose contributions and inspiration this package would not exist.

You can load and install nflfastR from GitHub with:

# If 'devtools' isn't installed run
# install.packages("devtools")

devtools::install_github("mrcaseb/nflfastR")

We have provided some application examples under vignette("examples"). However, these require a basic knowledge of R. For this reason we have the nflfastR beginner’s guide in vignette("beginners_guide"), which we recommend to all those who are looking for an introduction to nflfastR with R.

Even though nflfastR is very fast, for historical games we recommend downloading the data from here. These data sets include play-by-play data of complete seasons going back to 1999 and we will update them in 2020 once the season starts. The files contain both regular season and postseason data, and one can use game_type or week to figure out which games occurred in the postseason. Data are available as .csv.gz, .parquet, or .rds.

nflfastR uses its own models for Expected Points, Win Probability, and Completion Probability. To read about the models, please see vignette("nflfastR-models"). For a more detailed description of Expected Points models, we highly recommend this paper from the nflscrapR team located here.

nflfastR includes two win probability models: one with and one without incorporating the pre-game spread.

To Nick Shoemaker for finding and making available JSON-formatted NFL play-by-play back to 1999 (nflfastR uses this source for 1999-2010)
To Lau Sze Yui for developing a scraping function to access JSON-formatted NFL play-by-play beginning in 2011.
To Lee Sharpe for curating a resource for game information
To Timo Riske, Lau Sze Yui, Sean Clement, and Daniel Houston for many helpful discussions regarding the development of the new nflfastR models
To Zach Feldman and Josh Hermsmeyer for many helpful discussions about CPOE models as well as Peter Owen for many helpful suggestions for the CP model
To Florian Schmitt for the logo design
The many users who found and reported bugs in nflfastR 1.0
And of course, the original nflscrapR team, Maksim Horowitz, Ronald Yurko, and Samuel Ventura, whose work represented a dramatic step forward for the state of public NFL research