Articles • hoopR

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Basketball Advanced Metrics in R: Possessions, Pace, Ratings and the Four Factors: Compute possessions, pace, offensive, defensive and net rating, the four factors, eFG%, true shooting, usage and per-100 stats for NBA and college teams with hoopR.
CollegeBasketballData (CBD) Endpoints: A tour of the cbbd_* functions, which wrap the CollegeBasketballData API (api.collegebasketballdata.com) for men’s college basketball games, plays, stats, ratings, recruiting and more.
College Basketball Player Value Model: Box Plus-Minus for NCAA Men's Players: How the box plus-minus (BPM) ratings behind hoopR’s load_mbb_player_value() are built from box-score rates, how reliable they are, and how to use the qualified flag.
College Basketball RAPM Model: Regularized Adjusted Plus-Minus for NCAA Men's Players: How the league-wide and within-team NCAA men’s basketball RAPM ratings in hoopR are built from possessions and stints, how they validate, and how to fit RAPM yourself in R.
College Basketball Team Ratings Model: Opponent-Adjusted Efficiency for NCAA Men's Teams: How the opponent-adjusted offensive, defensive and tempo ratings behind hoopR’s load_mbb_ratings() are computed, checked and used, with reproducible R examples.
College Basketball Win Probability Model: In-Game Win Probability in hoopR Play-by-Play: How the home_win_prob and pregame_home_prob columns in hoopR’s men’s college basketball play-by-play are produced, how well they are calibrated, and how to plot a win probability chart.
ESPN basketball endpoints -- NBA & MBB: A tour of the 199 ESPN basketball endpoint wrappers in hoopR, grouped by use case: game data, team detail, athlete coverage, per-event enrichments, league-wide catalogs, NBA draft/transactions/free-agency endpoints, and the post-3.0.0 core-v2 deep expansion (athlete career, team-season stats, per-game player box, play personnel, typed-detail companions).
Getting Started with hoopR: NBA and College Basketball Data in R: Install hoopR and load NBA and men’s college basketball play-by-play, box scores, shots and model data in R, with a worked example, a glossary and next steps.
International Basketball Data in R: EuroLeague, FIBA and 40+ Leagues with hoopR: A guide to hoopR’s international basketball functions: EuroLeague, EuroCup, FIBA, ACB, NBL, B.League, KBL, LBA, CBA and more, with the data each league offers.
KenPom Example Functions: Some examples to get started with using hoopR and KenPom’s men’s college basketball website.
Men's College Basketball Cookbook: A storytelling tour of men’s college basketball analysis with hoopR – recipes from a single game to a full bracket, plus KenPom efficiency, and a running commentary on how to read the package’s function names.
NBA and College Basketball Shot Charts in R with hoopR, sportyR and sdvplotR: Draw NBA and men’s college basketball shot charts in R: make/miss plots, hexbin and density maps, shot zones and FG% by zone from hoopR shot data on sportyR courts.
NBA Cookbook: A storytelling tour of NBA analysis with hoopR – recipes that move from a single box score to a full season, with an eye on how the package’s function names are built so you can guess the next one before you look it up.
NBA Player Impact Model: RAPM, SPM, BPM, DARKO-Style Projections and WAR: How the SportsDataverse NBA player impact suite behind load_nba_player_impact() works: six engines from RAPM to WAR, how they are fit, how well they validate, and their limits.
NBA Stats API Parameter Descriptions: A searchable reference table of every query parameter used by the NBA Stats API endpoints wrapped in hoopR – parameter name, description, accepted values, and which functions accept it.