G-Elo: generalization of the Elo algorithm by modeling the discretized margin of victory
Author
Abstract
Suggested Citation
DOI: 10.1515/jqas-2020-0115
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Mark E. Glickman, 1999. "Parameter Estimation in Large Dynamic Paired Comparison Experiments," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 48(3), pages 377-394.
- Kovalchik, Stephanie, 2020. "Extension of the Elo rating system to margin of victory," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1329-1341.
- Ingram Martin, 2021. "How to extend Elo: a Bayesian perspective," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 17(3), pages 203-219, September.
- Gramacy Robert B. & Jensen Shane T. & Taddy Matt, 2013. "Estimating player contribution in hockey with regularized logistic regression," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 9(1), pages 97-111, March.
- Boshnakov, Georgi & Kharrat, Tarak & McHale, Ian G., 2017. "A bivariate Weibull count model for forecasting association football scores," International Journal of Forecasting, Elsevier, vol. 33(2), pages 458-466.
- Szczecinski Leszek & Djebbi Aymen, 2020. "Understanding draws in Elo rating algorithm," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 16(3), pages 211-220, September.
- 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, vol. 8(1), pages 1-14, March.
- Kovalchik Stephanie Ann, 2016. "Searching for the GOAT of tennis win prediction," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 12(3), pages 127-138, September.
- M. J. Maher, 1982. "Modelling association football scores," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 36(3), pages 109-118, September.
- Alan Agresti, 1992. "Analysis of Ordinal Paired Comparison Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 41(2), pages 287-297, June.
- 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.
- 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.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- László Csató, 2024. "Club coefficients in the UEFA Champions League: Time for shift to an Elo-based formula," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 24(2), pages 119-134, March.
- 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.
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.- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- J. James Reade & Carl Singleton & Alasdair Brown, 2019. "Evaluating Strange Forecasts: The Curious Case of Football Match Scorelines," Economics Discussion Papers em-dp2019-18, Department of Economics, University of Reading, revised 01 Aug 2020.
- Gross, Johannes & Rebeggiani, Luca, 2018.
"Chance or Ability? The Efficiency of the Football Betting Market Revisited,"
MPRA Paper
87230, University Library of Munich, Germany.
- Rebeggiani, Luca & Gross, Johannes, 2018. "Chance or Ability? The Efficiency of the Football Betting Market Revisited," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181563, Verein für Socialpolitik / German Economic Association.
- 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.
- 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.
- Philip Ramirez & J. James Reade & Carl Singleton, 2021. "Betting on a buzz, mispricing and inefficiency in online sportsbooks," Economics Discussion Papers em-dp2021-10, Department of Economics, University of Reading, revised 27 Jul 2022.
- 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.
- 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.
- Paolo Gorgi & Siem Jan Koopman & Rutger Lit, 2020. "Estimation of final standings in football competitions with premature ending: the case of COVID-19," Tinbergen Institute Discussion Papers 20-070/III, Tinbergen Institute.
- Kovalchik, Stephanie, 2020. "Extension of the Elo rating system to margin of victory," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1329-1341.
- 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.
- J. James Reade & Carl Singleton & Leighton Vaughan Williams, 2020. "Betting markets for English Premier League results and scorelines: evaluating a forecasting model," Economics Discussion Papers em-dp2020-03, Department of Economics, University of Reading.
- 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.
- 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.
- Song, Kai & Shi, Jian, 2020. "A gamma process based in-play prediction model for National Basketball Association games," European Journal of Operational Research, Elsevier, vol. 283(2), pages 706-713.
- 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.
- 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.
More about this item
Keywords
adjacent categories model; Elo algorithm; margin of victory; rating;All these keywords.
Statistics
Access and download statisticsCorrections
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:bpj:jqsprt:v:18:y:2022:i:1:p:1-14:n:5. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.