IDEAS home Printed from https://ideas.repec.org/r/eee/intfor/v26yi3p460-470.html
   My bibliography  Save this item

Using ELO ratings for match result prediction in association football

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Demers Simon, 2015. "Riding a probabilistic support vector machine to the Stanley Cup," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 11(4), pages 205-218, December.
  2. Hojun Sung & Brian M. Mills, 2018. "Estimation of game-level attendance in major league soccer: Outcome uncertainty and absolute quality considerations," Sport Management Review, Taylor & Francis Journals, vol. 21(5), pages 519-532, December.
  3. Kovalchik, Stephanie, 2020. "Extension of the Elo rating system to margin of victory," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1329-1341.
  4. S. E. Hill, 2022. "In-game win probability models for Canadian football," Journal of Business Analytics, Taylor & Francis Journals, vol. 5(2), pages 164-178, July.
  5. Paul Bose & Eberhard Feess & Helge Mueller, 2022. "Favoritism towards High-Status Clubs: Evidence from German Soccer," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 38(2), pages 422-478.
  6. Bruzzone, Octavio A. & Logarzo, Guillermo A. & Aguirre, María B. & Virla, Eduardo G., 2018. "Intra-host interspecific larval parasitoid competition solved using modelling and bayesian statistics," Ecological Modelling, Elsevier, vol. 385(C), pages 114-123.
  7. J Reade & C Singleton & L Vaughan Williams, 2020. "Betting Markets for English Premier League Results and Scorelines: Evaluating a Simple Forecasting Model," Economic Issues Journal Articles, Economic Issues, vol. 25(1), pages 87-106, March.
  8. Dmitry Dagaev & Sofia Paklina & J. James Reade & Carl Singleton, 2024. "The Iron Curtain and Referee Bias in International Football," Journal of Sports Economics, , vol. 25(1), pages 126-151, January.
  9. Restocchi, Valerio & McGroarty, Frank & Gerding, Enrico & Johnson, Johnnie E.V., 2018. "It takes all sorts: A heterogeneous agent explanation for prediction market mispricing," European Journal of Operational Research, Elsevier, vol. 270(2), pages 556-569.
  10. Sumit Sarkar & Sooraj Kamath, 2023. "Does luck play a role in the determination of the rank positions in football leagues? A study of Europe’s ‘big five’," Annals of Operations Research, Springer, vol. 325(1), pages 245-260, June.
  11. J. James Reade & Dominik Schreyer & Carl Singleton, 2020. "Echoes: what happens when football is played behind closed doors?," Economics Discussion Papers em-dp2020-14, Department of Economics, University of Reading.
  12. 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, H. O. Stekler Research Program on Forecasting.
  13. 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.
  14. Gross, Johannes & Rebeggiani, Luca, 2018. "Chance or Ability? The Efficiency of the Football Betting Market Revisited," MPRA Paper 87230, University Library of Munich, Germany.
  15. 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.
  16. 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.
  17. Subhasish M. Chowdhury & Sarah Jewell & Carl Singleton, 2023. "Can Awareness Reduce (and Reverse) Identity-driven Bias in Judgement? Evidence from International Cricket," Economics Discussion Papers em-dp2023-10, Department of Economics, University of Reading.
  18. 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.
  19. 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.
  20. Baboota, Rahul & Kaur, Harleen, 2019. "Predictive analysis and modelling football results using machine learning approach for English Premier League," International Journal of Forecasting, Elsevier, vol. 35(2), pages 741-755.
  21. Angelini, Giovanni & Candila, Vincenzo & De Angelis, Luca, 2022. "Weighted Elo rating for tennis match predictions," European Journal of Operational Research, Elsevier, vol. 297(1), pages 120-132.
  22. 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.
  23. Sarah Jewell & J. James Reade & Carl Singleton, 2020. "It's Just Not Cricket: The Uncontested Toss and the Gentleman's Game," Economics Discussion Papers em-dp2020-10, Department of Economics, University of Reading.
  24. Marius Ötting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2023. "Gambling on Momentum in Contests," Economics Discussion Papers em-dp2023-08, Department of Economics, University of Reading.
  25. Maria Bolsinova & Gunter Maris & Abe D. Hofman & Han L. J. van der Maas & Matthieu J. S. Brinkhuis, 2022. "Urnings: A new method for tracking dynamically changing parameters in paired comparison systems," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(1), pages 91-118, January.
  26. Alex Krumer & Juan D. Moreno-Ternero, 2023. "The Allocation of Additional Slots for the FIFA World Cup," Journal of Sports Economics, , vol. 24(7), pages 831-850, October.
  27. Stefan Szymanski & Jason Winfree, 2018. "On The Optimal Realignment Of A Contest: The Case Of College Football," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 483-496, January.
  28. Štrumbelj, Erik & Vračar, Petar, 2012. "Simulating a basketball match with a homogeneous Markov model and forecasting the outcome," International Journal of Forecasting, Elsevier, vol. 28(2), pages 532-542.
  29. He, Xue-Zhong & Treich, Nicolas, 2017. "Prediction market prices under risk aversion and heterogeneous beliefs," Journal of Mathematical Economics, Elsevier, vol. 70(C), pages 105-114.
  30. J. James Reade & Carl Singleton, 2020. "Demand for Public Events in the COVID-19 Pandemic: A Case Study of European Football," Economics Discussion Papers em-dp2020-09, Department of Economics, University of Reading, revised 01 Oct 2020.
  31. Peeters, Thomas, 2018. "Testing the Wisdom of Crowds in the field: Transfermarkt valuations and international soccer results," International Journal of Forecasting, Elsevier, vol. 34(1), pages 17-29.
  32. Roberto Gásquez & Vicente Royuela, 2016. "The Determinants of International Football Success: A Panel Data Analysis of the Elo Rating," Social Science Quarterly, Southwestern Social Science Association, vol. 97(2), pages 125-141, June.
  33. 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, vol. 9(1), pages 37-50, March.
  34. Oliver Engist & Erik Merkus & Felix Schafmeister, 2021. "The Effect of Seeding on Tournament Outcomes: Evidence From a Regression-Discontinuity Design," Journal of Sports Economics, , vol. 22(1), pages 115-136, January.
  35. László Csató, 2020. "The UEFA Champions League seeding is not strategy-proof since the 2015/16 season," Annals of Operations Research, Springer, vol. 292(1), pages 161-169, September.
  36. 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.
  37. 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.
  38. J. James Reade & Dominik Schreyer & Carl Singleton, 2022. "Eliminating supportive crowds reduces referee bias," Economic Inquiry, Western Economic Association International, vol. 60(3), pages 1416-1436, July.
  39. 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.
  40. L.F.M. Groot & J. Ferwerda, 2014. "Soccer jersey sponsors and the world cup," Working Papers 14-07, Utrecht School of Economics.
  41. Hvattum Lars Magnus, 2015. "Playing on artificial turf may be an advantage for Norwegian soccer teams," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 11(3), pages 183-192, September.
  42. Li, Yuesen & Ma, Runqing & Gonçalves, Bruno & Gong, Bingnan & Cui, Yixiong & Shen, Yanfei, 2020. "Data-driven team ranking and match performance analysis in Chinese Football Super League," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
  43. J. James Reade & Jan C. van Ours, 2024. "Consumer Perceptions Matter: A Case Study of an Anomaly in English Football," Economics Discussion Papers em-dp2024-03, Department of Economics, University of Reading.
  44. Ramirez, Philip & Reade, J. James & Singleton, Carl, 2023. "Betting on a buzz: Mispricing and inefficiency in online sportsbooks," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1413-1423.
  45. 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.
  46. 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.
  47. Vaughan Williams Leighton & Liu Chunping & Dixon Lerato & Gerrard Hannah, 2021. "How well do Elo-based ratings predict professional tennis matches?," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 17(2), pages 91-105, June.
  48. 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.
  49. Yamini Nekkanti & Dibyojyoti Bhattacharjee, 2020. "Novel Performance Metrics to Evaluate the Duel Between a Batsman and a Bowler," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 45(2), pages 201-211, May.
  50. L'aszl'o Csat'o, 2023. "Club coefficients in the UEFA Champions League: Time for shift to an Elo-based formula," Papers 2304.09078, arXiv.org, revised Oct 2023.
  51. 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.
  52. Csató, László & Bodnár, Gergely, 2023. "Mérhetnénk jobban a csapatok erejét a Bajnokok Ligájában? Fontos megjegyzés az Európai Labdarúgó-szövetség számára [How to better measure team strength in the Champions League. An important message," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 813-827.
  53. Luca Pappalardo & Paolo Cintia, 2018. "Quantifying The Relation Between Performance And Success In Soccer," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(03n04), pages 1-30, May.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.