New NBA dataset on Kaggle! - Every game 60,000+ (1946-2021) w/ box scores, line scores, series info, and more - every player 4500+ w/ draft data, career stats, biometrics, and more - and every team (30 w/ franchise histories, coaches/staffing, and more). Updated daily, with plans for expansion!

This page summarizes the projects mentioned and recommended in the original post on /r/kaggle

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  • nba_api

    An API Client package to access the APIs for NBA.com

  • The data is from stats.nba.com via the nba_api on GitHub. I compiled the data through an extraction script, and keep it updated daily via a fully automated Kaggle data pipeline. The pipeline is described here, and the project repository is here

  • sports-analytics

    Data collection, processing, visualization, modeling, and ideation in the space of sports analytics

  • The data is from stats.nba.com via the nba_api on GitHub. I compiled the data through an extraction script, and keep it updated daily via a fully automated Kaggle data pipeline. The pipeline is described here, and the project repository is here

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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  • NBA-attendance-prediction

    Attendance prediction tool for NBA games using machine learning. Full pipeline implemented in Python from data ingestion to prediction. Attained mean absolute error of around 800 people (about 5% capacity) on test set.

  • The current iteration contains attendance numbers through the Box Scores within the Game table. It's actually funny you ask about that particular feature; that was my inspiration for creating the dataset in general. I had previously scraped data from basketball-reference.com to use in order to create an attendance prediction tool for NBA stadium organization leaders and struggled to find reliable, robust data. However, via stats.nba.com, the attendance data is rather solid 👍

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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