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Forecasting Formula 1 race outcomes. Combines ML predictive modeling with data-driven visualizations to analyze grid positions, lap performance, and race dynamics.

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BLShaw/F1-Predictor

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F1 Predictor

A Formula 1 prediction engine combining Monte Carlo simulation with Machine Learning for Grand Prix outcomes.

Key Features

  • Grand Prix Centric: Organizes data by Season and Round.
  • ML / Monte Carlo: Uses Machine Learning to predict probabilistic outcomes (Win/Podium %).
  • SHAP Explainability: Explains why a driver is predicted to finish in a certain position.
  • Sprints: Full support for Sprint Weekends.

Clone the Repository

git clone https://github.com/BLShaw/f1-predictor.git

Install the dependencies

pip install -r requirements.txt

Run Application

streamlit run app.py

Screenshots

Screenshot_40 Screenshot_41 Screenshot_42 Screenshot_43 Screenshot_44 Screenshot_45 Screenshot_46 Screenshot_47 Screenshot_48

License

MIT License.

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Forecasting Formula 1 race outcomes. Combines ML predictive modeling with data-driven visualizations to analyze grid positions, lap performance, and race dynamics.

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