TL;DR • Key Features • Quickstart • Credits • License
https://github.com/user-attachments/assets/28b689f3-0b23-455b-a97a-b97ad0464d7a --- ## 📌 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. --- ## 💡 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** --- ## 🔑 Key Features * **Data-Driven Predictions** – Powered by real NBA stats from [Basketball Reference](https://www.basketball-reference.com). * **Real-Time Interface** – Visualize upcoming matchups and model predictions with a sleek NiceGUI web frontend. * **Weighted Stats Engine** – Uses Exponentially Weighted Moving Averages ([EWMA](https://en.wikipedia.org/wiki/EWMA_chart)) 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. --- ## ⚡ Quickstart ```bash 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 ``` --- ## 📬 Emailware: Share Your Thoughts DeepShot is [emailware](https://en.wiktionary.org/wiki/emailware). If it helps you or you find it interesting, I’d love to hear from you! Send feedback to: **[francescosacco.github@gmail.com](mailto:francescosacco.github@gmail.com)** --- ## 🙏 Love DeepShot? Support It! If this project helped you or you just think it’s cool: * ⭐️ Star the repo * 🧃 [Buy me a coffee](https://www.buymeacoffee.com/saccofrancesco) * 💌 Send your thoughts or suggestions by email --- ## 🧠 Credits & Acknowledgements DeepShot uses the following awesome libraries: * [Python](https://www.python.org/) * [Basketball Reference](https://www.basketball-reference.com) * [Requests](https://requests.readthedocs.io/en/latest/) * [BeautifulSoup](https://www.crummy.com/software/BeautifulSoup/bs4/doc/) * [Pandas](https://pandas.pydata.org) * [Scikit-Learn](https://scikit-learn.org/stable/) * [XGBoost](https://xgboost.readthedocs.io/en/release_3.0.0/) * [NiceGUI](https://nicegui.io) --- ## 📎 You Might Also Like... Check out more by the same author: * [Supremebot](https://github.com/saccofrancesco/supremebot): A user-friendly Supreme bot built with [NiceGUI](https://nicegui.io) to help you buy Supreme items effortlessly. --- ## 📜 License This project is licensed under the [MIT License](https://opensource.org/licenses/MIT) — feel free to use it in your own projects! --- > GitHub [@saccofrancesco](https://github.com/saccofrancesco)