IDEAS home Printed from https://ideas.repec.org/a/bla/stanee/v70y2016i3p260-273.html
   My bibliography  Save this article

An application of the generalized Poisson difference distribution to the Bayesian modelling of football scores

Author

Listed:
  • Golnaz Shahtahmassebi
  • Rana Moyeed

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
    • Handle: RePEc:bla:stanee:v:70:y:2016:i:3:p:260-273
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/stan.12087
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. M. J. Maher, 1982. "Modelling association football scores," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 36(3), pages 109-118, September.
    2. Andrew Gelman, 2003. "A Bayesian Formulation of Exploratory Data Analysis and Goodness‐of‐fit Testing," International Statistical Review, International Statistical Institute, vol. 71(2), pages 369-382, August.
    3. 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.
    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. Giulia Carallo & Roberto Casarin & Christian P. Robert, 2020. "Generalized Poisson Difference Autoregressive Processes," Papers 2002.04470, arXiv.org.
    2. Jacek Osiewalski & Jerzy Marzec, 2019. "Joint modelling of two count variables when one of them can be degenerate," Computational Statistics, Springer, vol. 34(1), pages 153-171, March.
    3. Santos-Fernandez Edgar & Wu Paul & Mengersen Kerrie L., 2019. "Bayesian statistics meets sports: a comprehensive review," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 15(4), pages 289-312, December.
    4. Federico Bassetti & Giulia Carallo & Roberto Casarin, 2022. "First-order integer-valued autoregressive processes with Generalized Katz innovations," Papers 2202.02029, arXiv.org.

    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. 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.
    2. 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.
    3. Haoying Wang & Guohui Wu, 2022. "Modeling discrete choices with large fine-scale spatial data: opportunities and challenges," Journal of Geographical Systems, Springer, vol. 24(3), pages 325-351, July.
    4. Holmes, Benjamin & McHale, Ian G. & Żychaluk, Kamila, 2023. "A Markov chain model for forecasting results of mixed martial arts contests," International Journal of Forecasting, Elsevier, vol. 39(2), pages 623-640.
    5. Scarf, Philip & Yusof, Muhammad Mat & Bilbao, Mark, 2009. "A numerical study of designs for sporting contests," European Journal of Operational Research, Elsevier, vol. 198(1), pages 190-198, October.
    6. Koning, Ruud H. & Koolhaas, Michael & Renes, Gusta & Ridder, Geert, 2003. "A simulation model for football championships," European Journal of Operational Research, Elsevier, vol. 148(2), pages 268-276, July.
    7. Gonzalez, Jhonny & Moriarty, John & Palczewski, Jan, 2017. "Bayesian calibration and number of jump components in electricity spot price models," Energy Economics, Elsevier, vol. 65(C), pages 375-388.
    8. Schwarz Wolf, 2012. "Predicting the Maximum Lead from Final Scores in Basketball: A Diffusion Model," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(4), pages 1-15, November.
    9. Csató, László, 2023. "How to avoid uncompetitive games? The importance of tie-breaking rules," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1260-1269.
    10. Babatunde Buraimo & David Forrest & Ian G. McHale & J.D. Tena, 2020. "Armchair Fans: New Insights Into The Demand For Televised Soccer," Working Papers 202020, University of Liverpool, Department of Economics.
    11. Stekler, H.O. & Sendor, David & Verlander, Richard, 2010. "Issues in sports forecasting," International Journal of Forecasting, Elsevier, vol. 26(3), pages 606-621, July.
      • Herman O. Stekler & David Sendor & Richard Verlander, 2009. "Issues in Sports Forecasting," Working Papers 2009-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    12. Deg-Hyo Bae & Kyung-Hwan Son & Jae-Min So, 2017. "Utilization of the Bayesian Method to Improve Hydrological Drought Prediction Accuracy," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(11), pages 3527-3541, September.
    13. Gianluca Baio & Marta Blangiardo, 2010. "Bayesian hierarchical model for the prediction of football results," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(2), pages 253-264.
    14. Clough, Brian J. & Russell, Matthew B. & Domke, Grant M. & Woodall, Christopher W. & Radtke, Philip J., 2016. "Comparing tree foliage biomass models fitted to a multispecies, felled-tree biomass dataset for the United States," Ecological Modelling, Elsevier, vol. 333(C), pages 79-91.
    15. Andrew Gelman & Christian Hennig, 2017. "Beyond subjective and objective in statistics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(4), pages 967-1033, October.
    16. 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.
    17. Leonardo Egidi & Nicola Torelli, 2021. "Comparing Goal-Based and Result-Based Approaches in Modelling Football Outcomes," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 801-813, August.
    18. László Csató, 2020. "Optimal Tournament Design: Lessons From the Men’s Handball Champions League," Journal of Sports Economics, , vol. 21(8), pages 848-868, December.
    19. 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.
    20. Buraimo, Babatunde & Forrest, David & McHale, Ian G. & Tena, J.D., 2022. "Armchair fans: Modelling audience size for televised football matches," European Journal of Operational Research, Elsevier, vol. 298(2), pages 644-655.

    More about this item

    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:bla:stanee:v:70:y:2016:i:3:p:260-273. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0039-0402 .

    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.