saccofrancesco / deepshot
AI-powered NBA game outcome predictor that uses advanced team stats and trend-based features to forecast winners and track model performance
Why this job: works in the areas we cover, but does not say which job it does
What it does
- Data-Driven Predictions. Powered by real NBA stats from Basketball Reference.
- Real-Time Interface. Visualize upcoming matchups and model predictions with a sleek NiceGUI web frontend.
- Weighted Stats Engine. Uses Exponentially Weighted Moving Averages (EWMA) to reflect recent performance trends.
- Key Stat Highlighting. Automatically surfaces differences between teams to help you identify strengths and weaknesses fast.
- Cross-Platform Support. Works smoothly on all major OSes.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit yesterday
- Stars
- 175
- On GitHub
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Jupyter Notebook
- 73% of the code
Is it looked after?
- Contributors
- 1
- Last 90 days
- Issues
- 100% closed
- 0 still open
- Pull requests
- 2 merged
- 0 waiting
- Releases
- None
- Never published
More: languages, topics and project record
Languages
- Jupyter Notebook 73%
- Python 27%
Topics
- basketball
- data-science
- machine-learning
- nba
- nba-predictions
- open-source
- pandas
- python
- xgboost
- ai
- feature-engineering
- jupyter-notebook
Project record
- JobOther AI tools
- StatusListed
- Commits1,324
- Forks22
- Watching4
- Stars in 28 days+4
- CreatedMar 19, 2025
- First seen by usNov 7, 2026
- CheckedNov 12, 2026