Faster identification of faster Formula 1 drivers via time-rank duality

Fry, John; Brighton, Tom; Fanzon, Silvio

Abstract

Two natural ways of modelling Formula 1 race outcomes are a probabilistic approach, based on the exponential distribution, and econometric modelling of the ranks. Both approaches lead to exactly soluble race-winning probabilities. Equating race-winning probabilities leads to a set of equivalent parametrisations. This time-rank duality is attractive theoretically and leads to quicker ways of disentangling driver and car level effects.

Citation

Fry, J., Brighton, T., & Fanzon, S. (2024). Faster identification of faster Formula 1 drivers via time-rank duality. Economics letters, 237, Article 111671. https://doi.org/10.1016/j.econlet.2024.111671

• Journal Article Type: Article
• Acceptance Date: Mar 20, 2024
• Online Publication Date: Mar 21, 2024
• Publication Date: Apr 1, 2024
• Deposit Date: Mar 21, 2024
• Publicly Available Date: Mar 27, 2024
• Journal: Economics Letters
• Print ISSN: 0165-1765
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 237
• Article Number: 111671
• DOI: https://doi.org/10.1016/j.econlet.2024.111671
• Keywords: Exponential distribution; Formula 1; Regression; Time-rank duality
• Public URL: https://hull-repository.worktribe.com/output/4609711