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Dynamic Bradley–Terry modelling of sports tournaments

Author

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  • Manuela Cattelan
  • Cristiano Varin
  • David Firth

Abstract

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Suggested Citation

  • Manuela Cattelan & Cristiano Varin & David Firth, 2013. "Dynamic Bradley–Terry modelling of sports tournaments," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(1), pages 135-150, January.
  • Handle: RePEc:bla:jorssc:v:62:y:2013:i:1:p:135-150
    DOI: j.1467-9876.2012.01046.x
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    File URL: http://hdl.handle.net/10.1111/j.1467-9876.2012.01046.x
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    Citations

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    Cited by:

    1. Araki, Kenji & Hirose, Yoshihiro & Komaki, Fumiyasu, 2019. "Paired comparison models with age effects modeled as piecewise quadratic splines," International Journal of Forecasting, Elsevier, vol. 35(2), pages 733-740.
    2. Lim, Alejandro & Chiang, Chin-Tsang & Teng, Jen-Chieh, 2021. "Estimating robot strengths with application to selection of alliance members in FIRST robotics competitions," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
    3. Golnaz Shahtahmassebi & Rana Moyeed, 2016. "An application of the generalized Poisson difference distribution to the Bayesian modelling of football scores," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(3), pages 260-273, August.
    4. Gerhard Tutz & Gunther Schauberger, 2015. "Extended ordered paired comparison models with application to football data from German Bundesliga," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(2), pages 209-227, April.
    5. Guironnet, Jean-Pascal, 2023. "Competitive intensity and industry performance of professional sports," Economic Modelling, Elsevier, vol. 126(C).
    6. Franceschet Massimo & Bozzo Enrico & Vidoni Paolo, 2017. "The temporalized Massey’s method," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 13(2), pages 37-48, June.
    7. Cristiano Varin & Manuela Cattelan & David Firth, 2016. "Statistical modelling of citation exchange between statistics journals," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(1), pages 1-63, January.
    8. Marc Garnica-Caparrós & Daniel Memmert & Fabian Wunderlich, 2022. "Artificial data in sports forecasting: a simulation framework for analysing predictive models in sports," Information Systems and e-Business Management, Springer, vol. 20(3), pages 551-580, September.
    9. Claus Thorn Ekstrøm & Andreas Kryger Jensen, 2023. "Having a ball: evaluating scoring streaks and game excitement using in-match trend estimation," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 295-311, March.
    10. Wunderlich, Fabian & Memmert, Daniel, 2020. "Are betting returns a useful measure of accuracy in (sports) forecasting?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 713-722.
    11. Koopman, Siem Jan & Lit, Rutger, 2019. "Forecasting football match results in national league competitions using score-driven time series models," International Journal of Forecasting, Elsevier, vol. 35(2), pages 797-809.
    12. Alexandra Grand & Regina Dittrich & Brian Francis, 2015. "Markov models of dependence in longitudinal paired comparisons: an application to course design," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 99(2), pages 237-257, April.
    13. Lasek, Jan & Gagolewski, Marek, 2021. "Interpretable sports team rating models based on the gradient descent algorithm," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1061-1071.
    14. Murray Thomas A., 2017. "Ranking ultimate teams using a Bayesian score-augmented win-loss model," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 13(2), pages 63-78, June.

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