DeepShot: Predict NBA Games with Machine Learning

An advanced NBA game predictor powered by historical data from Basketball Reference, rolling statistics, and machine learning — built with NiceGUI for a seamless experience.

TL;DR • Key Features • Quickstart • Credits • License

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📌 TL;DR

DeepShot is a machine learning-based NBA game predictor using advanced rolling stats (like EWMA) and real historical performance. It helps forecast matchups with visual insights and a clean interactive GUI.

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💡 Why DeepShot Stands Out

• Uses Exponentially Weighted Moving Averages (EWMA) to capture recent form and momentum
• Visually highlights the key statistical differences between teams
• Clean, real-time NiceGUI-powered web interface
• Works locally across platforms (Windows, macOS, Linux)
• Based entirely on free and public data

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🔑 Key Features

• 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.

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⚡ Quickstart

git clone https://github.com/saccofrancesco/deepshot.git
cd deepshot
pip install -r requirements.txt
# Train model by running the notebook
# Open `model.ipynb` and run the cell to generate `deepshot.pkl`
python main.py  # Launches the NiceGUI web app

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📬 Emailware: Share Your Thoughts

DeepShot is emailware. If it helps you or you find it interesting, I’d love to hear from you!

Send feedback to: francescosacco.github@gmail.com

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🙏 Love DeepShot? Support It!

If this project helped you or you just think it’s cool:

• ⭐️ Star the repo
• 🧃 Buy me a coffee
• 💌 Send your thoughts or suggestions by email

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🧠 Credits & Acknowledgements

DeepShot uses the following awesome libraries:

• Python
• Basketball Reference
• Requests
• BeautifulSoup
• Pandas
• Scikit-Learn
• XGBoost
• NiceGUI

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Check out more by the same author:

• Supremebot: A user-friendly Supreme bot built with NiceGUI to help you buy Supreme items effortlessly.

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📜 License

This project is licensed under the MIT License — feel free to use it in your own projects!

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GitHub @saccofrancesco