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Modelling association football scores

Citations

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Cited by:

  1. Radu Tunaru & Ephraim Clark & Howard Viney, 2005. "An option pricing framework for valuation of football players," Review of Financial Economics, John Wiley & Sons, vol. 14(3-4), pages 281-295.
  2. Koning, Ruud H., 1999. "The competitive balance in Dutch soccer," Research Report 99B04, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
  3. Mario Mechtel & Agnes Bäker & Tobias Brändle & Karin Vetter, 2011. "Red Cards," Journal of Sports Economics, , vol. 12(6), pages 621-646, December.
  4. 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.
  5. M Wright & N Hirotsu, 2003. "The professional foul in football: Tactics and deterrents," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(3), pages 213-221, March.
  6. Yuvraj Sunecher & Naushad Mamode Khan & Vandna Jowaheer & Marcelo Bourguignon & Mohammad Arashi, 2019. "A Primer on a Flexible Bivariate Time Series Model for Analyzing First and Second Half Football Goal Scores: The Case of the Big 3 London Rivals in the EPL," Annals of Data Science, Springer, vol. 6(3), pages 531-548, September.
  7. Scarf, Phil & Parma, Rishikesh & McHale, Ian, 2019. "On outcome uncertainty and scoring rates in sport: The case of international rugby union," European Journal of Operational Research, Elsevier, vol. 273(2), pages 721-730.
  8. Lahvicka, Jiri, 2013. "Impact of playoffs on seasonal uncertainty in Czech ice hockey Extraliga," MPRA Paper 44608, University Library of Munich, Germany.
  9. Patrice Marek & František Vávra, 2020. "Comparison of Home Advantage in European Football Leagues," Risks, MDPI, vol. 8(3), pages 1-13, August.
  10. Chater, Mario & Arrondel, Luc & Gayant, Jean-Pascal & Laslier, Jean-François, 2021. "Fixing match-fixing: Optimal schedules to promote competitiveness," European Journal of Operational Research, Elsevier, vol. 294(2), pages 673-683.
  11. Raffaele Mattera, 2023. "Forecasting binary outcomes in soccer," Annals of Operations Research, Springer, vol. 325(1), pages 115-134, June.
  12. 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.
  13. Cunniffe Nik J & Cook Alex R, 2009. "Cruel and Unusual Punishment? An Analysis of Point Deduction in European Association Football Leagues," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(4), pages 1-20, October.
  14. 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.
  15. Oberhofer, Harald & Philippovich, Tassilo & Winner, Hannes, 2010. "Distance matters in away games: Evidence from the German football league," Journal of Economic Psychology, Elsevier, vol. 31(2), pages 200-211, April.
  16. Sebastián Cea & Guillermo Durán & Mario Guajardo & Denis Sauré & Joaquín Siebert & Gonzalo Zamorano, 2020. "An analytics approach to the FIFA ranking procedure and the World Cup final draw," Annals of Operations Research, Springer, vol. 286(1), pages 119-146, March.
  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. Dobson, Stephen & Goddard, John, 2003. "Persistence in sequences of football match results: A Monte Carlo analysis," European Journal of Operational Research, Elsevier, vol. 148(2), pages 247-256, July.
  19. Geenens Gery, 2010. "Who Deserved the 2008-2009 Belgian Football Champion Title? A Semiparametric Answer," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(4), pages 1-31, October.
  20. Dixon, Mark J. & Pope, Peter F., 2004. "The value of statistical forecasts in the UK association football betting market," International Journal of Forecasting, Elsevier, vol. 20(4), pages 697-711.
  21. 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.
  22. Dagaev Dmitry & Rudyak Vladimir Yu., 2019. "Seeding the UEFA Champions League participants: evaluation of the reforms," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 15(2), pages 129-140, June.
  23. 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.
  24. 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.
  25. 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.
  26. Koning, R.H., 2000. "An econometric evaluation of the firing of a coach on team performance," Research Report 00F40, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
  27. 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.
  28. da Costa, Igor Barbosa & Marinho, Leandro Balby & Pires, Carlos Eduardo Santos, 2022. "Forecasting football results and exploiting betting markets: The case of “both teams to score”," International Journal of Forecasting, Elsevier, vol. 38(3), pages 895-909.
  29. Giovanni Angelini & Luca De Angelis, 2017. "PARX model for football match predictions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(7), pages 795-807, November.
  30. Melanie Krause & Stefan Szymanski, 2019. "Convergence versus the middle-income trap: the case of global soccer," Applied Economics, Taylor & Francis Journals, vol. 51(27), pages 2980-2999, June.
  31. Hans Eetvelde & Lars Magnus Hvattum & Christophe Ley, 2023. "The Probabilistic Final Standing Calculator: a fair stochastic tool to handle abruptly stopped football seasons," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 251-269, March.
  32. Chia-Hao Chang, 2021. "Construction of a Predictive Model for MLB Matches," Forecasting, MDPI, vol. 3(1), pages 1-11, February.
  33. 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.
  34. Federico Fioravanti & Fernando Tohmé & Fernando Delbianco & Alejandro Neme, 2021. "Effort of rugby teams according to the bonus point system: a theoretical and empirical analysis," International Journal of Game Theory, Springer;Game Theory Society, vol. 50(2), pages 447-474, June.
  35. R. H. Koning, 2003. "An econometric evaluation of the effect of firing a coach on team performance," Applied Economics, Taylor & Francis Journals, vol. 35(5), pages 555-564.
  36. 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.
  37. 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.
  38. Jeon, Gyuhyeon & Park, Juyong, 2021. "Characterizing patterns of scoring and ties in competitive sports," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
  39. repec:dgr:rugsom:01a65 is not listed on IDEAS
  40. Holmes, Benjamin & McHale, Ian G., 2024. "Forecasting football match results using a player rating based model," International Journal of Forecasting, Elsevier, vol. 40(1), pages 302-312.
  41. A D Fitt & C J Howls & M Kabelka, 2006. "Valuation of soccer spread bets," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(8), pages 975-985, August.
  42. Bäker Agnes & Mechtel Mario & Vetter Karin, 2012. "Beating thy Neighbor: Derby Effects in German Professional Soccer," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(3), pages 224-246, June.
  43. Rose D. Baker & Ian G. McHale, 2015. "Time varying ratings in association football: the all-time greatest team is.," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(2), pages 481-492, February.
  44. Hirotsu Nobuyoshi & Wright Mike B, 2006. "Modeling Tactical Changes of Formation in Association Football as a Zero-Sum Game," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 2(2), pages 1-22, April.
  45. Munđar Dušan & Šimić Diana, 2016. "Croatian First Football League: Teams' performance in the championship," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 2(1), pages 15-23, September.
  46. 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.
  47. Kharrat, Tarak & McHale, Ian G. & Peña, Javier López, 2020. "Plus–minus player ratings for soccer," European Journal of Operational Research, Elsevier, vol. 283(2), pages 726-736.
  48. Stephen T. Easton & Duane W. Rockerbie, 2005. "Overtime! Rules and Incentives in the National Hockey League," Journal of Sports Economics, , vol. 6(2), pages 178-202, May.
  49. Francisco Corona & Nelson Muriel & Jesús López-Pérez, 2023. "Who is the greatest team in Liga MX? A dynamic analysis/¿Cuál es el equipo más grande de la Liga MX? Un análisis dinámico," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 38(2), pages 225–260-2.
  50. Jiří LahviÄ ka, 2015. "Using Monte Carlo Simulation to Calculate Match Importance," Journal of Sports Economics, , vol. 16(4), pages 390-409, May.
  51. J. James Reade & Carl Singleton & Alasdair Brown, 2021. "Evaluating strange forecasts: The curious case of football match scorelines," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(2), pages 261-285, May.
  52. Gavin A. Whitaker & Ricardo Silva & Daniel Edwards & Ioannis Kosmidis, 2021. "A Bayesian approach for determining player abilities in football," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(1), pages 174-201, January.
  53. Leonardo Egidi & Ioannis Ntzoufras, 2020. "A Bayesian quest for finding a unified model for predicting volleyball games," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1307-1336, November.
  54. Corona Francisco & Horrillo Juan de Dios Tena & Wiper Michael Peter, 2017. "On the importance of the probabilistic model in identifying the most decisive games in a tournament," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 13(1), pages 11-23, March.
  55. Gross, Johannes & Rebeggiani, Luca, 2018. "Chance or Ability? The Efficiency of the Football Betting Market Revisited," MPRA Paper 87230, University Library of Munich, Germany.
  56. repec:dgr:rugsom:00f40 is not listed on IDEAS
  57. G. K. Skinner & G. H. Freeman, 2009. "Soccer matches as experiments: how often does the 'best' team win?," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(10), pages 1087-1095.
  58. Wheatcroft, Edward, 2020. "A profitable model for predicting the over/under market in football," LSE Research Online Documents on Economics 103712, London School of Economics and Political Science, LSE Library.
  59. 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.
  60. Robert C. Smit & Francesco Ravazzolo & Luca Rossini, 2020. "Dynamic Bayesian forecasting of English Premier League match results with the Skellam distribution," BEMPS - Bozen Economics & Management Paper Series BEMPS72, Faculty of Economics and Management at the Free University of Bozen.
  61. Bracewell Paul J & Forbes Don G. R. & Jowett Clint A. & Kitson Heath I. J., 2009. "Determining the Evenness of Domestic Sporting Competition Using a Generic Rating Engine," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(1), pages 1-25, January.
  62. Andreas Heuer & Oliver Rubner, 2014. "Optimizing the Prediction Process: From Statistical Concepts to the Case Study of Soccer," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-9, September.
  63. Szczecinski Leszek, 2022. "G-Elo: generalization of the Elo algorithm by modeling the discretized margin of victory," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 18(1), pages 1-14, March.
  64. I. Graham & H. Stott, 2008. "Predicting bookmaker odds and efficiency for UK football," Applied Economics, Taylor & Francis Journals, vol. 40(1), pages 99-109.
  65. 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.
  66. Hirotsu Nobuyoshi & Ito Masamitsu & Miyaji Chikara & Hamano Koji & Taguchi Azuma, 2009. "Modeling Tactical Changes of Formation in Association Football as a Non-Zero-Sum Game," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(3), pages 1-15, July.
  67. 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.
  68. 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.
  69. Riccardo Ievoli & Aldo Gardini & Lucio Palazzo, 2023. "The role of passing network indicators in modeling football outcomes: an application using Bayesian hierarchical models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 153-175, March.
  70. Siem Jan Koopman & Rutger Lit & André Lucas, 2014. "The Dynamic Skellam Model with Applications," Tinbergen Institute Discussion Papers 14-032/IV/DSF73, Tinbergen Institute, revised 06 Jul 2015.
  71. 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.
  72. Geenens, Gery, 2014. "On the decisiveness of a game in a tournament," European Journal of Operational Research, Elsevier, vol. 232(1), pages 156-168.
  73. Fry, John & Serbera, Jean-Philippe & Wilson, Rob, 2021. "Managing performance expectations in association football," Journal of Business Research, Elsevier, vol. 135(C), pages 445-453.
  74. N Hirotsu & M Wright, 2003. "Determining the best strategy for changing the configuration of a football team," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(8), pages 878-887, August.
  75. 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.
  76. Marta Boczoń & Alistair J. Wilson, 2023. "Goals, Constraints, and Transparently Fair Assignments: A Field Study of Randomization Design in the UEFA Champions League," Management Science, INFORMS, vol. 69(6), pages 3474-3491, June.
  77. repec:dgr:rugsom:99b04 is not listed on IDEAS
  78. 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.
  79. Jiří LahviÄ ka, 2015. "The Impact of Playoffs on Seasonal Uncertainty in the Czech Ice Hockey Extraliga," Journal of Sports Economics, , vol. 16(7), pages 784-801, October.
  80. Leitner, Christoph & Zeileis, Achim & Hornik, Kurt, 2010. "Forecasting sports tournaments by ratings of (prob)abilities: A comparison for the EUROÂ 2008," International Journal of Forecasting, Elsevier, vol. 26(3), pages 471-481, July.
  81. Forrest, David & Simmons, Robert, 2000. "Forecasting sport: the behaviour and performance of football tipsters," International Journal of Forecasting, Elsevier, vol. 16(3), pages 317-331.
  82. Wheatcroft, Edward, 2020. "A profitable model for predicting the over/under market in football," International Journal of Forecasting, Elsevier, vol. 36(3), pages 916-932.
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