Basketball

Tidy NBA, WNBA, and NCAA men's & women's basketball — play-by-play, box scores, schedules, rosters, and standings — via the cross-league espn_nba_* / espn_wnba_* / espn_mbb_* / espn_wbb_* wrappers, mirroring hoopR and wehoop.

Football

College football and the NFL: ESPN play-by-play, schedules, teams, and QBR through espn_cfb_* / espn_nfl_*, plus an nfl module that mirrors nflreadpy and reads nflverse releases. Aligned with cfbfastR.

Baseball

MLB across three surfaces — ESPN, the official MLB Stats API (mlb_api_*), and Baseball Savant / Statcast — for schedules, play-by-play, rosters, and pitch-level data. The Python companion to baseballr.

Hockey

NHL & PWHL via ESPN plus the NHL's own modern APIs: the api-web.nhle.com game feed (nhl_*), EDGE player tracking (nhl_edge_*), Stats REST, and the Records site — mirroring fastRhockey.

Tidy by default

Every wrapper returns raw JSON by default; opt into an analysis-ready polars (or pandas) DataFrame with return_parsed=True, a parse_* function, or the sportsdataverse.parsed.* mirror. Whole seasons load from pre-built parquet via load_*.

Part of the SportsDataverse

Free and open, with one mental model across sports and languages — the function you know in R is the call you make in Python — plus benchmarkable EP/WP models. See Ecosystem & philosophy for the full Python ↔ R map.