Formula 1 Race Winner Prediction Using Random Forest and SHAP Analysis

Elias El Haber; Elie Sawaya; Maroun Attieh; Aldo Tannous; Weam Ghazaly; Michel Owayjan

Year2025

Published in2025 International Conference on Control, Automation, and Instrumentation (IC2AI)

DepartmentComputer and Communications Engineering

DOI10.1109/IC2AI62984.2025.10932140

PublisherIEEE

Abstract

Predicting the outcomes of Formula 1 (F1) races presents a significant challenge due to the complex interplay of numerous factors, including driver skill, vehicle performance, team strategy, and unpredictable race-day conditions. This paper investigates the application of the Random Forest algorithm enhanced with SHAP (Shapley Additive Explanations) analysis to forecast race winners while providing interpretability to the model's predictions. By leveraging extensive historical data encompassing driver metrics and race conditions, we aim to build a model that achieves high predictive accuracy and offers valuable insights into the most influential factors affecting race outcomes. Our approach demonstrates how integrating machine learning with explainable AI techniques can assist F1 teams in making data-driven decisions, ultimately optimizing their strategies in the highly competitive environment of professional racing.

Keywords

Measurement Analytical models Explainable AI Instruments Decision making Predictive models Prediction algorithms Random forests Vehicles Sports

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E.E. Haber, E. Sawaya, M. Attieh, A. Tannous, W. Ghazaly, M. Owayjan, "Formula 1 Race Winner Prediction Using Random Forest and SHAP Analysis," 2025 International Conference on Control, Automation, and Instrumentation (IC2AI), 2025 doi: 10.1109/IC2AI62984.2025.10932140.

Haber, E.E., Sawaya, E., Attieh, M., Tannous, A., Ghazaly, W., & Owayjan, M. (2025). Formula 1 Race Winner Prediction Using Random Forest and SHAP Analysis. 2025 International Conference on Control, Automation, and Instrumentation (IC2AI). https://doi.org/10.1109/IC2AI62984.2025.10932140

Haber, Elias El, et al. "Formula 1 Race Winner Prediction Using Random Forest and SHAP Analysis." 2025 International Conference on Control, Automation, and Instrumentation (IC2AI), 2025. doi:10.1109/IC2AI62984.2025.10932140.

Haber, Elias El, and Elie Sawaya, and Maroun Attieh, and Aldo Tannous, and Weam Ghazaly, and Michel Owayjan. "Formula 1 Race Winner Prediction Using Random Forest and SHAP Analysis." 2025 International Conference on Control, Automation, and Instrumentation (IC2AI) (2025). https://doi.org/10.1109/IC2AI62984.2025.10932140.

Haber, E.E. et al. (2025) 'Formula 1 Race Winner Prediction Using Random Forest and SHAP Analysis', 2025 International Conference on Control, Automation, and Instrumentation (IC2AI). doi:10.1109/IC2AI62984.2025.10932140.

Haber EE, Sawaya E, Attieh M, Tannous A, Ghazaly W, Owayjan M. Formula 1 Race Winner Prediction Using Random Forest and SHAP Analysis. 2025 International Conference on Control, Automation, and Instrumentation (IC2AI). 2025. doi:10.1109/IC2AI62984.2025.10932140.

@inproceedings{haber2025,
  author    = {Haber, Elias El and Sawaya, Elie and Attieh, Maroun and Tannous, Aldo and Ghazaly, Weam and Owayjan, Michel},
  title     = {{Formula 1 Race Winner Prediction Using Random Forest and SHAP Analysis}},
  booktitle = {2025 International Conference on Control, Automation, and Instrumentation (IC2AI)},
  year      = {2025},
  publisher = {IEEE},
  doi       = {10.1109/IC2AI62984.2025.10932140},
}