I’m building a Formula 1 race predictor 🏎️ that pulls in historical data with FastF1, cleans and normalizes results, and updates driver rankings after every Grand Prix to forecast finishing orders. It’s a work in progress, and I’m constantly adding new features and improvements! 🚀
- Data ingestion: Pulls 2018–2024 race results via FastF1 API
- Data cleaning: Filters DNFs and standardizes finishing positions
- Elo engine: Initializes all drivers at 1500, updates after each GP, configurable K-factors for Sprint/Feature races
- Performance: Delivers ~10% accuracy gain over last season’s standings baseline
- Track Heatmap

Install the required Python packages with pip:
pip install -r requirements.txt- Integrate qualifying session ratings
- Build an interactive dashboard (Streamlit or React)
- Refine K-factor dynamics based on track characteristics
- Incorporate weather data to adjust prediction confidence
- Add live API endpoint for real-time race forecasts
- Improve accuracy (by a lot)
- 🌐 Website: [https://sites.google.com/psu.edu/]
- 🔗 LinkedIn: [https://www.linkedin.com/in/meeravshah/]
This project is licensed under the MIT License.