nflfastR

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.

Installation

You can load and install nflfastR from GitHub with:

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

devtools::install_github("mrcaseb/nflfastR")

Usage

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.

Data repository

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 models

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.

Special thanks