IDEAS home Printed from https://ideas.repec.org/a/bpj/jqsprt/v12y2016i2p99-112n3.html

Formula for success: Multilevel modelling of Formula One Driver and Constructor performance, 1950–2014

Author

Listed:
  • Bell Andrew

    (The University of Sheffield – Sheffield Methods Institute, Sheffield, United Kingdom of Great Britain and Northern Ireland)

  • Smith James

    (University of Bristol – School of Geographical Sciences, Bristol, United Kingdom of Great Britain and Northern Ireland)

  • Sabel Clive E.

    (University of Bristol – School of Geographical Sciences, Bristol, United Kingdom of Great Britain and Northern Ireland)

  • Jones Kelvyn

    (University of Bristol – School of Geographical Sciences, Bristol, United Kingdom of Great Britain and Northern Ireland)

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. The points scored by drivers in a race (standardised across seasons and Normalised) is used as the response variable in a cross-classified multilevel model that partitions variance into team, team-year and driver levels. These effects are then allowed to vary by year, track type and weather conditions using complex variance functions. Juan Manuel Fangio is found to be the greatest driver of all time. Team effects are shown to be more important than driver effects (and increasingly so over time), although their importance may be reduced in wet weather and on street tracks. A sensitivity analysis was undertaken with various forms of the dependent variable; this did not lead to substantively different conclusions. We argue that the approach can be applied more widely across the social sciences, to examine individual and team performance under changing conditions.

Suggested Citation

  • Bell Andrew & Smith James & Sabel Clive E. & Jones Kelvyn, 2016. "Formula for success: Multilevel modelling of Formula One Driver and Constructor performance, 1950–2014," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 12(2), pages 99-112, June.
    • Handle: RePEc:bpj:jqsprt:v:12:y:2016:i:2:p:99-112:n:3
    DOI: 10.1515/jqas-2015-0050
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/jqas-2015-0050
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.1515/jqas-2015-0050?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. repec:bla:jomstd:v:47:y:2010:i:s1:p:884-910 is not listed on IDEAS
    2. A. Anderson, 2014. "Maximum likelihood ranking in racing sports," Applied Economics, Taylor & Francis Journals, vol. 46(15), pages 1778-1787, May.
    3. Anders Skrondal & Sophia Rabe-Hesketh, 2003. "Multilevel logistic regression for polytomous data and rankings," Psychometrika, Springer;The Psychometric Society, vol. 68(2), pages 267-287, June.
    4. Chris Judde & Ross Booth & Robert Brooks, 2013. "Second Place Is First of the Losers," Journal of Sports Economics, , vol. 14(4), pages 411-439, August.
    5. Rose D. Baker & Ian G. McHale, 2015. "Deterministic Evolution of Strength in Multiple Comparisons Models: Who is the Greatest Golfer?," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 180-196, March.
    6. Alnaser, W.E. & Probert, S.D. & El-Masri, S. & Al-Khalifa, S.E. & Flanagan, R. & Alnaser, N.W., 2006. "Bahrain's Formula-1 racing circuit: energy and environmental considerations," Applied Energy, Elsevier, vol. 83(4), pages 352-370, April.
    7. Reiner Eichenberger & David Stadelmann, 2009. "Who Is The Best Formula 1 Driver? An Economic Approach to Evaluating Talent," Economic Analysis and Policy, Elsevier, vol. 39(3), pages 389-406, December.
    8. Bell, Andrew & Jones, Kelvyn, 2015. "Explaining Fixed Effects: Random Effects Modeling of Time-Series Cross-Sectional and Panel Data," Political Science Research and Methods, Cambridge University Press, vol. 3(1), pages 133-153, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mourao, Paulo Reis, 2018. "Surviving in the shadows—An economic and empirical discussion about the survival of the non-winning F1 drivers," Economic Analysis and Policy, Elsevier, vol. 59(C), pages 54-68.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Onur Burak Celik, 2020. "Survival of Formula One Drivers," Social Science Quarterly, Southwestern Social Science Association, vol. 101(4), pages 1271-1281, July.
    2. Duane W. Rockerbie & Stephen T. Easton, 2022. "Race to the podium: separating and conjoining the car and driver in F1 racing," Applied Economics, Taylor & Francis Journals, vol. 54(54), pages 6272-6285, November.
    3. D'ora Gr'eta Petr'oczy & L'aszl'o Csat'o, 2019. "Revenue allocation in Formula One: a pairwise comparison approach," Papers 1909.12931, arXiv.org, revised Dec 2020.
    4. Ester Gutiérrez & Sebastián Lozano, 2020. "Benchmarking Formula One auto racing circuits: a two stage DEA approach," Operational Research, Springer, vol. 20(4), pages 2059-2083, December.
    5. Denly, Michael & Helms, Benjamin, 2025. "A Report on "Corruption and Co-optation in Autocracy: Evidence from Russia"," I4R Discussion Paper Series 260, The Institute for Replication (I4R).
    6. Gutiérrez-Romero, Roxana & Ahamed, Mostak, 2021. "COVID-19 response needs to broaden financial inclusion to curb the rise in poverty," World Development, Elsevier, vol. 138(C).
    7. Alessio Buonomo & Cinzia Conti & Francesca Di Patrizio & Salvatore Strozza & Marco Dionisio Terribili, 2024. "Distance learning during the pandemic: opinions and attitudes of young students," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 78(2), pages 211-220, April-Jun.
    8. Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2004. "GLLAMM Manual," U.C. Berkeley Division of Biostatistics Working Paper Series 1160, Berkeley Electronic Press.
    9. Wu, Yu & Mullan, Katrina & Biggs, Trent & Caviglia-Harris, Jill L. & Harris, Daniel & Sills, Erin O., "undated". "Do Forests Provide Watershed Services to Local Populations in the Humid Tropics? Evidence from the Brazilian Amazon," 2018 Annual Meeting, August 5-7, Washington, D.C. 274012, Agricultural and Applied Economics Association.
    10. Dominik Schreyer & Benno Torgler, 2018. "On the Role of Race Outcome Uncertainty in the TV Demand for Formula 1 Grands Prix," Journal of Sports Economics, , vol. 19(2), pages 211-229, February.
    11. Phuong V. Nguyen & Hien Thi Ngoc Huynh & Hoa Doan Xuan Trieu & Khoa T. Tran, 2019. "Internationalization, Strategic Slack Resources, and Firm Performance: The Case Study of Vietnamese Enterprises," JRFM, MDPI, vol. 12(3), pages 1-24, September.
    12. Roxana Gutiérrez-Romero, 2020. "Conflict in Africa during COVID-19: social distancing, food vulnerability and welfare response," Working Papers 104, Queen Mary, University of London, School of Business and Management, Centre for Globalisation Research.
    13. Patrick Velte, 2025. "Audit Quality and Materiality Disclosure Quality in Integrated Reporting: The Moderating Effect of Carbon Assurance Quality," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 32(3), pages 3785-3801, May.
    14. Tubiana, Matteo & Miguelez, Ernest & Moreno, Rosina, 2022. "In knowledge we trust: Learning-by-interacting and the productivity of inventors," Research Policy, Elsevier, vol. 51(1).
    15. van Kesteren Erik-Jan & Bergkamp Tom, 2023. "Bayesian analysis of Formula One race results: disentangling driver skill and constructor advantage," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 19(4), pages 273-293, December.
    16. Zhang, Jingwen & Zhang, Yanan & Bennett, Matthew R., 2025. "Spousal characteristics and unmet care needs: A longitudinal national study of adults aged 50 and over in England," Social Science & Medicine, Elsevier, vol. 365(C).
    17. Abduljalil Misbah Jummah Ahfeeth & Ayşem Çelebi, 2025. "Environmental Fines and Corporate Sustainability: The Moderating Role of Governance, Firm Size, and Institutional Ownership," Sustainability, MDPI, vol. 17(20), pages 1-23, October.
    18. Kutubi, Shawgat S. & Ahmed, Kamran & Khan, Hayat, 2018. "Bank performance and risk-taking — Does directors' busyness matter?," Pacific-Basin Finance Journal, Elsevier, vol. 50(C), pages 184-199.
    19. Kasraian, Dena & Maat, Kees & van Wee, Bert, 2018. "Urban developments and daily travel distances: Fixed, random and hybrid effects models using a Dutch pseudo-panel over three decades," Journal of Transport Geography, Elsevier, vol. 72(C), pages 228-236.
    20. Di Ciommo, Floridea & Comendador, Julio & López-Lambas, María Eugenia & Cherchi, Elisabetta & Ortúzar, Juan de Dios, 2014. "Exploring the role of social capital influence variables on travel behaviour," Transportation Research Part A: Policy and Practice, Elsevier, vol. 68(C), pages 46-55.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:jqsprt:v:12:y:2016:i:2:p:99-112:n:3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyterbrill.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.