[r/ML] [P] Using residual ML correction on top of a deterministic physics simulator for F1 strategy prediction

Summary

A CSE student developed F1Predict, a race simulation and strategy intelligence system for Formula 1. It integrates a deterministic physics simulator for baseline lap times with a LightGBM residual model, trained on historical telemetry, to correct pace deltas. The system then uses 10,000-iteration Monte Carlo simulations to produce probabilistic race outcome predictions for drivers.

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