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

John Fry, Tom Brighton and Silvio Fanzon

Economics Letters, 2024, vol. 237, issue C

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 dis-entangling driver and car level effects.

Keywords: Exponential distribution; Formula 1; Regression; Time-rank duality (search for similar items in EconPapers)
JEL-codes: C1 L8 Z2 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:237:y:2024:i:c:s016517652400154x

DOI: 10.1016/j.econlet.2024.111671

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