This dataset is updated daily and contains data on all games, all teams, and all players within the NBA including: 60,000+ games (every game since the first NBA season in 1946-47) including for the games in which the statistics were recorded: Box scores, Game summaries, Officials, Inactive players, Linescores, Last face-off stats, Season series ...
This dataset contains data about NCAA Basketball games, teams, and players. Game data covers play-by-play and box scores back to 2009, as well as final scores back to 1996. Additional data about wins and losses goes back to the 1894-5 season in some teams' cases.
NBA Basketball Datasets. NBA Player and Play by Play datasets in CSV Format – perfect for machine learning / sports data analysis & visualization, and building sportsbetting prediction models. NBA Player List (CSV) Data for every player to have ever played in the NBA, and each player’s player id. NBA Player list CSV
NBA Historical play-by-play data in CSV format dating back to 2004-05 season. The datasets include five-man lineups on the floor, play descriptions, shot-distance, and shot-location in X, Y coordinates.
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Previous game id of the team in the top slot of an NCAA tournament game. Used for rendering. BottomTeamPreviousGameId from 2019: integer: 32: Yes: Yes: Yes: Previous game id of the team in the bottom slot of an NCAA tournament game. Used for rendering. Channel: string: 10: Yes: No: Yes: The television station broadcasting the game: NeutralVenue ...
SportsDataIO provides a helpful guide that explains the data points within version 3 of the NBA Basketball API. Contact our Support Team with any questions you may have!
This repo contains two datasets (clips->.mp4 files and joints -> .npy files) of basketball single-player actions. In Figure below, a histogram of the number of examples is shown for every class. The size of the two final annotated datasets is about 32'560 examples, which can represent the basis for the subsequent training and testing phases for a classification of basket-like actions through Deep Neural Networks.