sports-analytics
nba-stats-analysis
| sports-analytics | nba-stats-analysis | |
|---|---|---|
| 1 | 1 | |
| 32 | 2 | |
| - | - | |
| 2.6 | 2.7 | |
| about 3 years ago | almost 3 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
sports-analytics
-
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!
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
nba-stats-analysis
-
Weekly Friday Self-Promotion and Fan Art Thread
I have been using it to make some analytics job on a couple of different points, as I start reading sources like Dean Oliver's Basketball on Paper, and have been uploading it to my GitHub repo. The format is in Jupyter Notebooks, so if anyone is familiar with Python, you can run it on your own computers.
What are some alternatives?
nba-sql - :basketball: An application to build an NBA database backed by MySQL, Postgres, or SQLite
nba_api - An API Client package to access the APIs for NBA.com
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.
fastai - The fastai deep learning library
homemade-machine-learning - 🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
football_analytics - 📊⚽ A collection of football analytics projects, data, and analysis by Edd Webster (@eddwebster), including a curated list of publicly available resources published by the football analytics community.
Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.
football-crunching - Analysis and datasets about football (soccer)
TensorFlow-Examples - TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)