| ---
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| license: apache-2.0
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| language:
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| - en
|
| tags:
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| - formula-1
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| - motorsport
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| - race-strategy
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| - multi-agent
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| - langgraph
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| - xgboost
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| - lightgbm
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| - temporal-convolutional-network
|
| - sports-analytics
|
| ---
|
|
|
| # F1 StratLab Strategy Models
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|
|
| The machine learning models behind F1 StratLab, an open-source multi-agent system for
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| Formula 1 race strategy. Six LangGraph sub-agents and a ReAct orchestrator call these
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| models to produce pit-stop recommendations, tire-degradation forecasts, overtake and
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| undercut probabilities, and answers grounded in the FIA regulations.
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|
|
| Links:
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|
|
| - Project: https://f1stratlab.com
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| - Documentation: https://docs.f1stratlab.com
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| - Source code: https://github.com/VforVitorio/F1-StratLab
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| - Dataset: https://huggingface.co/datasets/VforVitorio/f1-strategy-dataset
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|
|
| ## Models
|
|
|
| | Task | Algorithm | Metric |
|
| |---|---|---|
|
| | Lap-time prediction | XGBoost | MAE 0.392 s |
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| | Tire degradation | TCN with Monte Carlo Dropout | P10/P50/P90 quantiles, pit-window detection |
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| | Overtake probability | LightGBM | AUC-ROC 0.876 |
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| | Safety-car probability | LightGBM | classifier |
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| | Pit-stop duration | HistGradientBoosting (quantile) | MAE 0.487 s |
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| | Undercut success | LightGBM (binary) | AUC-ROC 0.771 |
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| | Team-radio NLP | Whisper, RoBERTa, SetFit, BERT-large | 4-stage pipeline |
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|
|
| ## Training data
|
|
|
| Trained on telemetry, lap data and race-control messages from 71 Grand Prix across the
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| 2023 to 2025 seasons, taken from the FastF1 and OpenF1 public APIs. The processed data is
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| published as a companion dataset: VforVitorio/f1-strategy-dataset.
|
|
|
| ## Intended use
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|
|
| Research and educational use for Formula 1 strategy analysis. Not affiliated with Formula 1,
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| the FIA or any team. Predictions are estimates, not guarantees.
|
|
|
| ## Citation
|
|
|
| ```bibtex
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| @misc{vegasobral2026f1stratlab,
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| author = {Vega, V{\'i}ctor},
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| title = {F1 StratLab: AI Models for Strategy Recommendations in Formula 1 Races},
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| year = {2026},
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| note = {Bachelor's Thesis, Intelligent Systems Engineering, UIE Campus Coru{\~n}a},
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| url = {https://f1stratlab.com}
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| }
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| ```
|
|
|
| ## License
|
|
|
| Apache 2.0. Author: Víctor Vega (https://github.com/VforVitorio).
|
|
|
