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F1 StratLab Strategy Dataset
Training data for F1 StratLab, an open-source multi-agent system for Formula 1 race strategy. It contains telemetry, lap data, tire stints and race-control messages turned into model-ready features for lap-time prediction, tire-degradation modelling, overtake and undercut probability, pit-stop duration and team-radio NLP.
Links:
- Project: https://f1stratlab.com
- Documentation: https://docs.f1stratlab.com
- Source code: https://github.com/VforVitorio/F1-StratLab
- Models: https://huggingface.co/VforVitorio/f1-strategy-models
Coverage
- 71 Grand Prix, 2023 to 2025 seasons.
- Sources: FastF1 and OpenF1 public APIs.
- Per-lap telemetry, tire compound and age, stint structure, gaps and race-control events.
Intended use
Research and educational use for Formula 1 strategy analysis and time-series or tabular ML. Not affiliated with Formula 1, the FIA or any team. Raw data is subject to the terms of the upstream FastF1 and OpenF1 sources.
Citation
@misc{vegasobral2026f1stratlab,
author = {Vega, V{\'i}ctor},
title = {F1 StratLab: AI Models for Strategy Recommendations in Formula 1 Races},
year = {2026},
note = {Bachelor's Thesis, Intelligent Systems Engineering, UIE Campus Coru{\~n}a},
url = {https://f1stratlab.com}
}
License
Apache 2.0. Author: Víctor Vega (https://github.com/VforVitorio).
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