Forecasting football results and the efficiency of fixed‐odds betting

By John Goddard, Ioannis G. Asimakopoulos. 2004

217 citations recorded by the source corpus.

Subfields: Clinical Psychology, Economics and Econometrics, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/77d4d54ead5d2855a96a29d608d4fa5c775a5f31

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In Clinical Psychology

In Economics and Econometrics

In Sociology and Political Science

Citations in the corpus

Dynamic Bradley–Terry modelling of sports tournaments (2013, methodology): “Goddard and Asimakopoulos (2004) used an ordered probit model to determine which covariates, e.g. importance of the match, fouls, yellow and red cards, affect the result of the match.”
Sports forecasting: a comparison of the forecast accuracy of prediction markets, betting odds and tipsters (2009, background): “However, Goddard and Asimakopoulos (2004) reveal, in the context of English soccer league matches during the 1999–2000 season, that considering additional information, such as previous outcomes, team quality indicators and geographical distance between the teams, leads to betting strategies with a…”
Are football referees really biased and inconsistent?: evidence on the incidence of disciplinary sanction in the English Premier League (2007, methodology): “Maher (1982), Dixon and Coles (1997), Dixon and Pope (2004) and Goddard (2005) used the bivariate Poisson distribution to model English football goal scoring data, whereas Cain et al.”
Using ELO ratings for match result prediction in association football (2010, methodology): “An ordered probit regression model with several types of explanatory variables was presented for this purpose by Goddard and Asimakopoulos (2004).”
Forecasting football match results in national league competitions using score-driven time series models (2019, methodology): “A selection of covariates can be introduced in both the static ordered probit regression model of Goddard and Asimakopoulos (2004) and the static ordered logit model of Forrest and Simmons (2000).”
How Efficient is the European Football Betting Market? Evidence from Arbitrage and Trading Strategies (2009, methodology): “and Coles (1997) and Goddard and Asimakopoulos (2004), reported substantial out-of-sample profits from strategies based on Poisson and ordered probit models, respectively.”
Issues in Sports Forecasting (2010, methodology): “The win ratios of the two teams playing the match were included as independent variables in the model of Goddard and Asimakopoulos (2004).”
Modelling the dependence of goals scored by opposing teams in international soccer matches (2011, unknown): “The models may also be useful in other contexts such as analysing the efficiency of the soccer betting market (e.g., Goddard and Asimakopoulos, 2004), judging the skills of tipsters at predicting match outcomes (Forrest and Simmons, 2000) and assessing the effect of red cards (Ridder et al., 1994).”