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

Fry, John; Brighton, Tom; Fanzon, Silvio

Authors

Profile image of John Fry

Dr John Fry J.M.Fry@hull.ac.uk
Senior Lecturer in Applied Mathematics

Tom Brighton



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

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