hoopR is an R package for
working with men’s basketball data.
The package has functions to access live play by play and box score
data from ESPN with shot locations when available. As of version 1.3.0,
hoopR is also a full NBA
Stats API wrapper with 127 functions added in this release.
It is additionally a scraping and aggregating interface for Ken Pomeroy’s men’s college basketball statistics website, kenpom.com. It provides users with an active subscription the capability to scrape the website tables and analyze the data for themselves.
As of version 3.1.0, the package exports 600+ functions spanning the NBA
Stats API (nba_*), ESPN (espn_nba_* / espn_mbb_*), KenPom
(kp_*), CollegeBasketballData (cbbd_*), Basketball-Reference
(bref_*), Bart Torvik (torvik_*), RealGM (realgm_*), Fox Sports
(fox_*), NCAA (ncaa_mbb_*), and NBA G-League (nbagl_*), plus
load_nba_*() / load_mbb_*() / load_ncaa_mbb_*() bulk-data loaders
backed by the sportsdataverse-data release repos.
The load_*() functions read release assets on
sportsdataverse-data.
The badges below are rebuilt nightly from each producer’s latest
workflow run and newest release files; idle means the sport is out of
season. Full detail:
sportsdataverse.org/status.
| Dataset | Data updated | Through | Pipeline | Update workflows |
|---|---|---|---|---|
| Men’s college basketball (ESPN) |  |
 |
 |
  |
| Men’s college basketball (stats.ncaa.org) |  |
 |
 |
 |
| NBA (ESPN) |  |
 |
 |
 |
| NBA Stats API |  |
 |
 |
   |
| Conference, division and ballpark reference |  |
 |
 |
— |
You can install the CRAN version of
hoopR with:
install.packages("hoopR")You can install the released version of
hoopR from
GitHub with:
# You can install using the pak package using the following code:
if (!requireNamespace('pak', quietly = TRUE)){
install.packages('pak')
}
pak::pak("sportsdataverse/hoopR")tictoc::tic()
progressr::with_progress({
nba_pbp <- hoopR::load_nba_pbp()
})
tictoc::toc()## 4.05 sec elapsed
## 642472 rows of NBA play-by-play data from 1325 games.
tictoc::tic()
progressr::with_progress({
mbb_pbp <- hoopR::load_mbb_pbp()
})
tictoc::toc()## 12.98 sec elapsed
## 2915731 rows of men's college basketball play-by-play data from 6275 games.
For more information on the package and function reference, please see
the hoopR documentation
website.
There is also a printable hoopR cheat sheet (PDF), one of a set covering every SportsDataverse package.
- Saiem Gilani (@saiemgilani)
-
Jason Lee (@theFirmAISports)
-
Billy Fryer (@BillyFryer42)
-
Ross Drucker (@rossdrucker9)
-
Vladislav Shufinskiy (@vshufinskiy)
A printable one-page reference for hoopR — the function families, the loaders, and what each one returns.
📄 Download the hoopR cheat sheet (PDF)
Free to download, print and hand out; light and dark, US Letter landscape. Every SportsDataverse package has one — browse them all at sportsdataverse.org/cheatsheets.
To cite the hoopR R package
in publications, use:
BibTex Citation
@misc{gilani_2021_hoopR,
author = {Gilani, Saiem},
title = {hoopR: The SportsDataverse's R Package for Men's Basketball Data.},
url = {https://hoopR.sportsdataverse.org},
doi = {10.32614/CRAN.package.hoopR},
year = {2026}
}