A data-driven project to explore Formula 1 trends, analyze performance, and build predictive models aimed at optimizing F1 Fantasy team selection — all in pursuit of my first fantasy league win.
This project began as a simple exercise to learn dynamic programming and solve a knapsack-style problem: picking the best possible F1 Fantasy team under budget. It quickly grew into a tool to benchmark my weekly picks against the optimal selection.
Next, I plan to integrate machine learning to predict top-performing teams using performance trends and track data.
Ensure your datasets are organized within a root directory. For example, place your files under ./data.
Run the main script with the root directory as an argument:
python main.py ./data