IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v40y2025i4d10.1007_s00180-024-01542-w.html
   My bibliography  Save this article

Kendall correlations and radar charts to include goals for and goals against in soccer rankings

Author

Listed:
  • Roy Cerqueti

    (Sapienza University of Rome
    University of Angers)

  • Raffaele Mattera

    (Sapienza University of Rome)

  • Valerio Ficcadenti

    (London South Bank University)

Abstract

This paper deals with the challenging themes of the way sporting teams and athletes are ranked in sports competitions. Starting from the paradigmatic case of soccer, we advance a new method for ranking teams in the official national championships through computational statistics methods based on Kendall correlations and radar charts. In detail, we consider the goals for and against the teams in the individual matches as a further source of score assignment beyond the usual win-tie-lose trichotomy. Our approach overcomes some biases in the scoring rules that are currently employed. The methodological proposal is tested over the relevant case of the Italian “Serie A” championships played during 1930–2023.

Suggested Citation

  • Roy Cerqueti & Raffaele Mattera & Valerio Ficcadenti, 2025. "Kendall correlations and radar charts to include goals for and goals against in soccer rankings," Computational Statistics, Springer, vol. 40(4), pages 1849-1872, April.
    • Handle: RePEc:spr:compst:v:40:y:2025:i:4:d:10.1007_s00180-024-01542-w
    DOI: 10.1007/s00180-024-01542-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00180-024-01542-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00180-024-01542-w?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. Valerio Ficcadenti & Roy Cerqueti & Ciro Hosseini Varde’i, 2023. "A rank-size approach to analyse soccer competitions and teams: the case of the Italian football league “Serie A"," Annals of Operations Research, Springer, vol. 325(1), pages 85-113, June.
    2. H. V. Ribeiro & R. S. Mendes & L. C. Malacarne & S. Picoli & P. A. Santoro, 2010. "Dynamics of tournaments: the soccer case," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 75(3), pages 327-334, June.
    3. Rose Baker & Philip Scarf, 2006. "Predicting the outcomes of annual sporting contests," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(2), pages 225-239, April.
    4. Poojan Thakkar & Manan Shah, 2021. "An Assessment of Football Through the Lens of Data Science," Annals of Data Science, Springer, vol. 8(4), pages 823-836, December.
    5. Richard J. Boys & Peter M. Philipson, 2019. "On the ranking of test match batsmen," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 68(1), pages 161-179, January.
    6. Marcel Ausloos & Rudi Cloots & Adam Gadomski & Nikolay K. Vitanov, 2014. "Ranking structures and rank–rank correlations of countries: The FIFA and UEFA cases," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 25(11), pages 1-17.
    7. P. Gorgi & S. J. Koopman & R. Lit, 2023. "Estimation of final standings in football competitions with a premature ending: the case of COVID-19," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 233-250, March.
    8. Balázs R Sziklai & Károly Héberger, 2020. "Apportionment and districting by Sum of Ranking Differences," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-20, March.
    9. R. S. Mendes & L. C. Malacarne & C. Anteneodo, 2007. "Statistics of football dynamics," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 57(3), pages 357-363, June.
    10. Manlio Migliorati & Marica Manisera & Paola Zuccolotto, 2023. "Integration of model-based recursive partitioning with bias reduction estimation: a case study assessing the impact of Oliver’s four factors on the probability of winning a basketball game," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 271-293, March.
    11. Raffaele Mattera, 2023. "Forecasting binary outcomes in soccer," Annals of Operations Research, Springer, vol. 325(1), pages 115-134, June.
    12. Ausloos, Marcel, 2024. "Hierarchy selection: New team ranking indicators for cyclist multi-stage races," European Journal of Operational Research, Elsevier, vol. 314(2), pages 807-816.
    13. Roy Cerqueti & P. d'Urso & L. de Giovanni & R. Mattera & V. Vitale, 2022. "INGARCH-based fuzzy clustering of count time series with a football application," Post-Print hal-04321538, HAL.
    14. Gabel Alan & Redner Sidney, 2012. "Random Walk Picture of Basketball Scoring," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(1), pages 1-20, March.
    15. Marco Sandri & Paola Zuccolotto & Marica Manisera, 2020. "Markov switching modelling of shooting performance variability and teammate interactions in basketball," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1337-1356, November.
    16. David Strauss & Barry C. Arnold, 1987. "The Rating of Players in Racquetball Tournaments," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 36(2), pages 163-173, June.
    17. Mattia Cefis & Maurizio Carpita, 2024. "The higher-order PLS-SEM confirmatory approach for composite indicators of football performance quality," Computational Statistics, Springer, vol. 39(1), pages 93-116, February.
    Full references (including those not matched with items on IDEAS)

    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. Paola Zuccolotto & Marco Sandri & Marica Manisera, 2023. "Spatial performance analysis in basketball with CART, random forest and extremely randomized trees," Annals of Operations Research, Springer, vol. 325(1), pages 495-519, June.
    2. Haroldo V Ribeiro & Satyam Mukherjee & Xiao Han T Zeng, 2016. "The Advantage of Playing Home in NBA: Microscopic, Team-Specific and Evolving Features," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-18, March.
    3. Devriesere, Karel & Csató, László & Goossens, Dries, 2025. "Tournament design: A review from an operational research perspective," European Journal of Operational Research, Elsevier, vol. 324(1), pages 1-21.
    4. Narizuka, Takuma & Yamamoto, Ken & Yamazaki, Yoshihiro, 2014. "Statistical properties of position-dependent ball-passing networks in football games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 412(C), pages 157-168.
    5. Puppe, Clemens & Tasnádi, Attila, 2025. "Violin virtuosi: Do their performances fade over time?," Working Paper Series in Economics 171, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    6. Rakhal Das & Binod Chandra Tripathy, 2024. "Separation Axioms on Spatial Topological Space and Spatial Data Analysis," Annals of Data Science, Springer, vol. 11(2), pages 411-423, April.
    7. Davy Paindaveine & Yvik Swan, 2009. "A stochastic analysis of some two-person sports," Working Papers ECARES 2009_025, ULB -- Universite Libre de Bruxelles.
    8. Carlota Torrents & Angel Ric & Robert Hristovski & Lorena Torres-Ronda & Emili Vicente & Jaime Sampaio, 2016. "Emergence of Exploratory, Technical and Tactical Behavior in Small-Sided Soccer Games when Manipulating the Number of Teammates and Opponents," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-15, December.
    9. dos Santos, M.A.F. & Colombo, E.H. & Anteneodo, C., 2021. "Random diffusivity scenarios behind anomalous non-Gaussian diffusion," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    10. Llorenç Badiella & Pedro Puig & Carlos Lago-Peñas & Martí Casals, 2023. "Influence of Red and Yellow cards on team performance in elite soccer," Annals of Operations Research, Springer, vol. 325(1), pages 149-165, June.
    11. J. James Reade, 2023. "Large Sporting Events and Public Health and Safety," Economics Discussion Papers em-dp2023-04, Department of Economics, University of Reading.
    12. Friedrich L. Sell & Jürgen Stiefl, 2021. "Missing the Popular Vote: Pitfalls in US Democracy and Reform Proposals," Intereconomics: Review of European Economic Policy, Springer;ZBW - Leibniz Information Centre for Economics;Centre for European Policy Studies (CEPS), vol. 56(4), pages 237-242, July.
    13. Valerio Ficcadenti & Roy Cerqueti & Ciro Hosseini Varde’i, 2023. "A rank-size approach to analyse soccer competitions and teams: the case of the Italian football league “Serie A"," Annals of Operations Research, Springer, vol. 325(1), pages 85-113, June.
    14. Léo Régnier & Maxim Dolgushev & Olivier Bénichou, 2023. "Record ages of non-Markovian scale-invariant random walks," Nature Communications, Nature, vol. 14(1), pages 1-7, December.
    15. Antonello D’Ambra & Pietro Amenta & Antonio Lucadamo, 2025. "Multivariate approaches to investigate the home and away behavior of football teams playing football matches," Computational Statistics, Springer, vol. 40(4), pages 1779-1799, April.
    16. Ausloos, Marcel, 2020. "Rank–size law, financial inequality indices and gain concentrations by cyclist teams. The case of a multiple stage bicycle race, like Tour de France," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    17. Tal Neiman & Yonatan Loewenstein, 2014. "Spatial Generalization in Operant Learning: Lessons from Professional Basketball," PLOS Computational Biology, Public Library of Science, vol. 10(5), pages 1-8, May.
    18. Alessandro Chessa & Pierpaolo D’Urso & Livia Giovanni & Vincenzina Vitale & Alfonso Gebbia, 2023. "Complex networks for community detection of basketball players," Annals of Operations Research, Springer, vol. 325(1), pages 363-389, June.
    19. Paola Zuccolotto & Marco Sandri & Marica Manisera, 2021. "Spatial Performance Indicators and Graphs in Basketball," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 725-738, August.
    20. David Winkelmann & Rouven Michels & Christian Deutscher, 2025. "Predicting Qualification Thresholds in UEFA's incomplete round-robin tournaments," Papers 2508.20075, arXiv.org, revised Sep 2025.

    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:spr:compst:v:40:y:2025:i:4:d:10.1007_s00180-024-01542-w. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.