{"url":"/dataset/nba-box-scores-odds","name":"NBA_Box_Scores_Odds","full_name":"NBA Team-Level Box Score Statistics (2015-2019), Historical Win Percentages (2014-2018) and Betting Odds (2018/2019)","description_markdown":"# Dataset Description: NBA Team Statistics, Historical Performance & Betting Odds (2015-2019)\r\n## Overview\r\nThis dataset contains team-level box score statistics, historical win percentages, and closing betting odds for NBA games from 2015 to 2019. It supports research in sports analytics, predictive modeling, and betting market efficiency.\r\n\r\n## Contents\r\nBox Score Statistics (2015-2019): Points, rebounds, assists, turnovers, shooting percentages, etc.\r\nHistorical Team Performance (2014-2018): Each team’s winning percentage over five seasons.\r\nBetting Odds (2018-2019): Closing moneyline odds and more\r\n\r\n## Use Cases\r\nPredictive Modeling: Forecasting NBA game outcomes using historical data.\r\nBetting Market Analysis: Evaluating odds efficiency in capturing true probabilities.\r\nSports Analytics: Analyzing trends in team performance and statistical patterns.","description_withheld":null,"homepage":"https://github.com/conorwalsh99/ml-for-sports-betting/tree/main/data/input","introduced_date":"2025-02-12","introduced_date_note":null,"introduced_by":{"paper":"/paper/machine-learning-for-sports-betting-should","title":"Machine learning for sports betting: should model selection be based on accuracy or calibration?","first_author":"Conor Walsh","url":null},"license":{"name":"MIT","url":"https://github.com/conorwalsh99/ml-for-sports-betting/blob/main/LICENSE"},"modalities":[{"name":"Tabular","url":"/datasets/modality/tabular"}],"tasks":[{"name":"Classification","url":"/task/classification-1","datasets_with_task":"/datasets/task/classification-1"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["NBA_Box_Scores_Odds"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}