Table of Contents generated with DocToc

• hoopR
  • Installation
  • Quick Start
    • NBA full play-by-play seasons (2002-2025) ~ 1-2 minutes
    • Men’s college basketball full play-by-play seasons (2006-2025) ~ 2-3 minutes
  • Documentation
  • Breaking Changes
  • Follow the SportsDataverse (@SportsDataverse) on Twitter and star this repo
  • Our Authors
  • Our Contributors (they’re awesome)
  • Citations

hoopR

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.

Installation

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")

Quick Start

NBA full play-by-play seasons (2002-2025) ~ 1-2 minutes

tictoc::tic()
progressr::with_progress({
  nba_pbp <- hoopR::load_nba_pbp()
})
tictoc::toc()

## 3.55 sec elapsed

## 615581 rows of NBA play-by-play data from 1305 games.

Men’s college basketball full play-by-play seasons (2006-2025) ~ 2-3 minutes

tictoc::tic()
progressr::with_progress({
  mbb_pbp <-  hoopR::load_mbb_pbp()
})
tictoc::toc()

## 6.94 sec elapsed

## 2112541 rows of men's college basketball play-by-play data from 5915 games.

Documentation

For more information on the package and function reference, please see the hoopR documentation website.

Breaking Changes

Full News on Releases

• Legacy nbagl_* wrappers now follow NBA Stats-backed payload structures.
• nbagl_players() and nbagl_standings() return named lists of data frames (PlayerIndex, Standings) instead of legacy flat schema assumptions.
• nbagl_schedule() and nbagl_pbp() return modernized core columns aligned with current upstream sources.

Follow the SportsDataverse (@SportsDataverse) on Twitter and star this repo

Our Authors

• Saiem Gilani (@saiemgilani)

Our Contributors (they’re awesome)

• Jason Lee (@theFirmAISports)

  

• Billy Fryer (@_b4billy_)

  

• Ross Drucker (@rossdrucker9)

  

• Vladislav Shufinskiy (@vshufinskiy)

  

Citations

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},
  year = {2021}
}