---
license: mit
tags:
- xgboost
- lightgbm
- sports-prediction
- formula1
- tabular
- classification
- ensemble
- optuna
language:
- en
---

# Telemetry Chaos — F1 Race Prediction Model

XGBoost + LightGBM ensemble predicting Formula 1 race winners from 76 seasons of historical data. Tuned with Optuna hyperparameter optimization across 200 trials. Auto-retrains weekly during the active season.

**Live demo:** [telemetrychaos.space](https://telemetrychaos.space)

## Performance

| Metric | Score |
|---|---|
| Top-1 Accuracy | 53% |
| Top-3 Accuracy | 85% |
| Top-5 Accuracy | 96% |

Evaluated on 2024–2025 seasons with time-series split to prevent data leakage.

## Features (21 per driver per race)

- **Form:** Rolling average points, recent podiums, win streak
- **Pace:** Practice session lap time delta vs. teammate and field
- **Constructor:** Team rolling performance, reliability score
- **Track history:** Driver-specific circuit win rate, podium rate
- **Tyre:** Degradation profile, pit stop speed, strategy tendency
- **Conditions:** Weather forecast, safety car probability
- **Grid:** Starting position, qualifying gap to pole

## Architecture

```
XGBoost (GPU) + LightGBM
Optuna HPO: 200 trials, TPE sampler
Time-series split: train on seasons N-5 to N-1, evaluate on N
Final output: softmax win probabilities per driver
```

## Dataset

- **Coverage:** 1950–2025, 76 seasons
- **Records:** 1,322,914 race records
- **Telemetry laps:** 470K+
- **Sources:** FastF1, Jolpica-F1, f1db, Kaggle

## Usage

```python
import joblib

model = joblib.load("f1_ensemble.joblib")
# Input: 21-feature vector per driver
# Output: win probability (0-1)
probs = model.predict_proba(X)
```

## Auto-Update Pipeline

During the active F1 season the model retrains weekly:
1. Pull latest race results and telemetry via FastF1
2. Engineer features for upcoming race grid
3. Retrain ensemble with updated data
4. Publish updated predictions to telemetrychaos.space

## Citation

```bibtex
@misc{rubin2026telemetrychaos,
  author = {Rubin, Theodore},
  title = {Telemetry Chaos: F1 Race Prediction with XGBoost/LightGBM Ensemble},
  year = {2026},
  publisher = {HuggingFace},
  url = {https://huggingface.co/datamatters24/f1-race-predictor-model}
}
```