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Regression models for forecasting goals and match results in association football

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  • Goddard, John

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  • Goddard, John, 2005. "Regression models for forecasting goals and match results in association football," International Journal of Forecasting, Elsevier, vol. 21(2), pages 331-340.
  • Handle: RePEc:eee:intfor:v:21:y:2005:i:2:p:331-340
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    References listed on IDEAS

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    1. Forrest, David & Simmons, Robert, 2000. "Forecasting sport: the behaviour and performance of football tipsters," International Journal of Forecasting, Elsevier, pages 317-331.
    2. Ioannis Asimakopoulos & John Goddard, 2004. "Forecasting football results and the efficiency of fixed-odds betting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(1), pages 51-66.
    3. P. Glewwe, 1997. "A test of the normality assumption in ordered probit model," Econometric Reviews, Taylor & Francis Journals, pages 1-19.
    4. Audas, Rick & Dobson, Stephen & Goddard, John, 2002. "The impact of managerial change on team performance in professional sports," Journal of Economics and Business, Elsevier, pages 633-650.
    5. Dixon, Mark J. & Pope, Peter F., 2004. "The value of statistical forecasts in the UK association football betting market," International Journal of Forecasting, Elsevier, pages 697-711.
    6. Tim Kuypers, 2000. "Information and efficiency: an empirical study of a fixed odds betting market," Applied Economics, Taylor & Francis Journals, vol. 32(11), pages 1353-1363.
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    Cited by:

    1. Oberhofer, Harald & Philippovich, Tassilo & Winner, Hannes, 2010. "Distance matters in away games: Evidence from the German football league," Journal of Economic Psychology, Elsevier, pages 200-211.
    2. Ian McHale & Rose Baker, 2014. "Econometric modelling of match results and scores," Chapters,in: Handbook on the Economics of Professional Football, chapter 9, pages 130-140 Edward Elgar Publishing.
    3. Barajas, Angel & Fernández-Jardón, Carlos & Crolley, Liz, 2005. "Does sports performance influence revenues and economic results in Spanish football?," MPRA Paper 3234, University Library of Munich, Germany.
    4. Heiner Matthew & Fellingham Gilbert W. & Thomas Camille, 2014. "Skill importance in women’s soccer," Journal of Quantitative Analysis in Sports, De Gruyter, pages 1-16.
    5. Lahvicka, Jiri, 2013. "Impact of playoffs on seasonal uncertainty in Czech ice hockey Extraliga," MPRA Paper 44608, University Library of Munich, Germany.
    6. repec:eee:intfor:v:34:y:2018:i:1:p:17-29 is not listed on IDEAS
    7. Tena Horrillo, Juan de Dios & Wiper, Michael Peter & Forrest, David & Corona, Francisco, 2017. "Evaluating significant effects from alternative seeding systems : a Bayesian approach, with an application to the UEFA Champions League," DES - Working Papers. Statistics and Econometrics. WS 24521, Universidad Carlos III de Madrid. Departamento de Estadística.
    8. Forrest, David & Goddard, John & Simmons, Robert, 2005. "Odds-setters as forecasters: The case of English football," International Journal of Forecasting, Elsevier, vol. 21(3), pages 551-564.
    9. 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, Research Program on Forecasting.
    10. O'Leary, Daniel E., 2017. "Crowd performance in prediction of the World Cup 2014," European Journal of Operational Research, Elsevier, vol. 260(2), pages 715-724.
    11. Constantinou Anthony Costa & Fenton Norman Elliott, 2013. "Determining the level of ability of football teams by dynamic ratings based on the relative discrepancies in scores between adversaries," Journal of Quantitative Analysis in Sports, De Gruyter, pages 37-50.
    12. Forrest, David & Sanz, Ismael & Tena, J.D., 2010. "Forecasting national team medal totals at the Summer Olympic Games," International Journal of Forecasting, Elsevier, vol. 26(3), pages 576-588, July.
    13. Siem Jan Koopman & Rutger Lit, 2015. "A dynamic bivariate Poisson model for analysing and forecasting match results in the English Premier League," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(1), pages 167-186, January.
    14. Rómulo A. Chumacero, 2009. "Altitude or Hot Air?," Journal of Sports Economics, , vol. 10(6), pages 619-638, December.
    15. John Goddard & Peter Sloane (ed.), 2014. "Handbook on the Economics of Professional Football," Books, Edward Elgar Publishing, number 14821, September.
    16. Schwarz Wolf, 2012. "Predicting the Maximum Lead from Final Scores in Basketball: A Diffusion Model," Journal of Quantitative Analysis in Sports, De Gruyter, pages 1-15.
    17. Siem Jan (S.J.) Koopman & Rutger Lit, 2017. "Forecasting Football Match Results in National League Competitions Using Score-Driven Time Series Models," Tinbergen Institute Discussion Papers 17-062/III, Tinbergen Institute.
    18. Hvattum, Lars Magnus & Arntzen, Halvard, 2010. "Using ELO ratings for match result prediction in association football," International Journal of Forecasting, Elsevier, vol. 26(3), pages 460-470, July.
    19. Bäker Agnes & Vetter Karin & Mechtel Mario, 2012. "Beating thy Neighbor: Derby Effects in German Professional Soccer," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, pages 224-246.
    20. J. James Reade & Sachiko Akie, 2013. "Using Forecasting to Detect Corruption in International Football," Working Papers 2013-005, The George Washington University, Department of Economics, Research Program on Forecasting.
    21. James Reade, 2014. "Detecting corruption in football," Chapters,in: Handbook on the Economics of Professional Football, chapter 25, pages 419-446 Edward Elgar Publishing.
    22. del Corral, Julio & Prieto-Rodríguez, Juan, 2010. "Are differences in ranks good predictors for Grand Slam tennis matches?," International Journal of Forecasting, Elsevier, vol. 26(3), pages 551-563, July.
    23. Constantinou Anthony Costa & Fenton Norman Elliott, 2012. "Solving the Problem of Inadequate Scoring Rules for Assessing Probabilistic Football Forecast Models," Journal of Quantitative Analysis in Sports, De Gruyter, pages 1-14.
    24. Hvattum Lars Magnus, 2015. "Playing on artificial turf may be an advantage for Norwegian soccer teams," Journal of Quantitative Analysis in Sports, De Gruyter, pages 183-192.
    25. Nikolaus Beck & Mark Meyer, 2012. "Modeling team performance," Empirical Economics, Springer, pages 335-356.

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