🏁 Formula 1 Las Vegas Grand Prix Simulation

This project combines racing passion with data analytics. Using EA Sports F1 23, I simulated the Las Vegas Grand Prix as Carlos Sainz, captured race telemetry, and explored key performance metrics via data visualization.

🎮 Simulation Setup

• Game: EA Sports F1 23
• Driver: Carlos Sainz
• Track: Las Vegas Grand Prix (night race, 50% race length)
• Data collected: Lap times, tire compound usage, fuel consumption, sector timings, final positions

📊 Visualizations

• Starting Grid vs Final Race Positions
  Highlights overtakes, pit strategy, and how qualifying affected final outcome.

• Lap Time Consistency
  Tracks improvement and degradation lap-by-lap.

• Tire Compounds Used
  Visualizes stint strategy: softs, mediums, tire wear impacts.

🔍 Key Insights

• Sainz gained +3 positions through early pit strategy on mediums
• Lap 12 showed fastest sector time—great tire performance window
• Consistent lap times despite high tire wear in final stint

📂 Project Structure

├── data/ # Cleaned telemetry data ├── notebooks/ # Jupyter notebooks for visualization ├── PDF/ # Images of plots and charts

🧠 Conclusion

Formula 1 teams process 20–40TB of data per race weekend. Visualizing that data — even in a simulation — helps uncover hidden performance insights and race strategy.

📎 Credits

• Simulation & Data: EA Sports F1 23
• Visualizations: Python, Matplotlib, Seaborn

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🏎️ Built with ❤️ for racing + data science.