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Are football referees really biased and inconsistent?: evidence on the incidence of disciplinary sanction in the English Premier League

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  • Peter Dawson
  • Stephen Dobson
  • John Goddard
  • John Wilson

Abstract

Summary. The paper presents a statistical analysis of patterns in the incidence of disciplinary sanction (yellow and red cards) that were taken against players in the English Premier League over the period 1996–2003. Several questions concerning sources of inconsistency and bias in refereeing standards are examined. Evidence is found to support a time consistency hypothesis, that the average incidence of disciplinary sanction is predominantly stable over time. However, a refereeing consistency hypothesis, that the incidence of disciplinary sanction does not vary between referees, is rejected. The tendency for away teams to incur more disciplinary points than home teams cannot be attributed to the home advantage effect on match results and appears to be due to a refereeing bias favouring the home team.

Suggested Citation

  • Peter Dawson & Stephen Dobson & John Goddard & John Wilson, 2007. "Are football referees really biased and inconsistent?: evidence on the incidence of disciplinary sanction in the English Premier League," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(1), pages 231-250, January.
    • Handle: RePEc:bla:jorssa:v:170:y:2007:i:1:p:231-250
    DOI: 10.1111/j.1467-985X.2006.00451.x
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    References listed on IDEAS

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    1. Michael Cain & David Law & David Peel, 2000. "The Favourite‐Longshot Bias and Market Efficiency in UK Football betting," Scottish Journal of Political Economy, Scottish Economic Society, vol. 47(1), pages 25-36, February.
    2. Luis Garicano & Ignacio Palacios-Huerta & Canice Prendergast, 2005. "Favoritism Under Social Pressure," The Review of Economics and Statistics, MIT Press, vol. 87(2), pages 208-216, May.
    3. Sutter, Matthias & Kocher, Martin G., 2004. "Favoritism of agents - The case of referees' home bias," Journal of Economic Psychology, Elsevier, vol. 25(4), pages 461-469, August.
    4. 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.
    5. Andrews, Donald W K, 2001. "Testing When a Parameter Is on the Boundary of the Maintained Hypothesis," Econometrica, Econometric Society, vol. 69(3), pages 683-734, May.
    6. W. David Allen, 2002. "Crime, Punishment, and Recidivism," Journal of Sports Economics, , vol. 3(1), pages 39-60, February.
    7. 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.
    8. 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.
    9. McCormick, Robert E & Tollison, Robert D, 1984. "Crime on the Court," Journal of Political Economy, University of Chicago Press, vol. 92(2), pages 223-235, April.
    10. 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.
    11. Heckman, James J, 1984. "The x[superscript]2 Goodness of Fit Statistic for Models with Parameters Estimated from Microdata," Econometrica, Econometric Society, vol. 52(6), pages 1543-1547, November.
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