See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/274080402 Formula for success: Multilevel modelling of Formula One Driver and Constructor performance, 1950-2014 Article in Journal of Quantitative Analysis in Sports · June 2016 DOI: 10.1515/jqas-2015-0050 CITATIONS READS 11 37,856 4 authors: Andrew Bell James Smith The University of Sheffield University of Bristol 36 PUBLICATIONS 1,111 CITATIONS 1 PUBLICATION 11 CITATIONS SEE PROFILE SEE PROFILE Clive E Sabel Kelvyn Jones Aarhus University University of Bristol 119 PUBLICATIONS 2,353 CITATIONS 255 PUBLICATIONS 8,425 CITATIONS SEE PROFILE SEE PROFILE Some of the authors of this publication are also working on these related projects: Multilevel modelling: scope, models and issues View project Multilevel modelling of mental health outcomes View project All content following this page was uploaded by Kelvyn Jones on 08 November 2017. The user has requested enhancement of the downloaded file. Formula for success: Multilevel modelling of Formula One Driver and Constructor performance, 1950-2014 Andrew Bell1, James Smith2, Clive E. Sabel2, Kelvyn Jones2 1Sheffield Methods Institute, The University of Sheffield 2School of Geographical Sciences, University of Bristol Draft – please do not cite without permission Last updated: 23rd March 2016 Corresponding author: Andrew Bell Sheffield Methods Institute Interdisciplinary Centre of the Social Sciences The University of Sheffield 219 Portobello Sheffield, S1 4DP
[email protected] Acknowledgements: Thanks to anonymous reviewers, Rick Stafford, and the Bristol University Spatial Modelling Research Group, for their helpful comments and advice. 1 Abstract This paper uses random-coefficient models and (a) finds rankings of who are the best formula 1 (F1) drivers of all time, conditional on team performance; (b) quantifies how much teams and drivers matter; and (c) quantifies how team and driver effects vary over time and under different racing conditions.