Are football referees really biased and inconsistent? Evidence from the English Premier League

This paper presents a statistical analysis of patterns in the incidence of disciplinary sanction (yellow and red cards) taken against players in the English Premier League over the period 1996-2003, using bivariate negative binomial and bivariate Poisson regressions. 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.UnpublishedAllen, W.D. (2002). Crime, punishment and recidivism: lessons from the National Hockey League. Journal of Sports Economics 3, 39-60. Cain, M., Law, D. and Peel, D. (2000). The favourite-longshot bias and market efficiency in UK football betting. Scottish Journal of Political Economy 47, 25-36. Deloitte and Touche (2004). Annual Review of Football Finance. Manchester: Deloitte. Dixon, M.J. and Coles, S.C. (1997). Modelling association football scores and inefficiencies in the football betting market. Applied Statistics 46, 265-280. Dixon, M.J. and Pope, P.F. (2004). The value of statistical forecasts in the UK association football betting market. International Journal of Forecasting 20, 697-711. Dobson, S. and Goddard, J. (2001). The economics of football. Cambridge: Cambridge University Press. Forrest, D., Goddard, J. and Simmons, R. (2005). Odds setters as forecasters: the case of English football. International Journal of Forecasting, forthcoming. Garicano, L. and Palacios-Huerta, I. (2000). An empirical examination of multidimensional effort in tournaments. Graduate School of Business, University of Chicago, mimeo. Garicano, L., Palacios-Huerta, I. and Prendergast, C. (2001). Favoritism under social pressure. NBER Working Paper 8376. Goddard, J. (2005). Regression models for forecasting goals and match results in association football. International Journal of Forecasting (forthcoming). Goddard, J. and Asimakopoulos, I. (2004). Forecasting football match results and the efficiency of fixed-odds betting. Journal of Forecasting 23, 51-66. Heckelman, J.C. and Yates, A.C. (2002). And a hockey game broke out: crime and punishment in the NHL. Economic Inquiry 41, 705-712. Karlis, D. and Ntzoufras, I. (2003). Analysis of sports data by using bivariate Poisson models. The Statistician 52, 381-393. Lee, A. (1999). Modelling rugby league data via bivariate negative binomial regression. Australian and New Zealand Journal of Statistics 41, 153-171. Maher, M.J. (1982). Modelling association football scores. Statistica Neerlandica 36, 109-118. McCormick, R.E. and Tollison, R.D. (1984). Crime on the court. Journal of Political Economy 92, 223-235. Nevill, A.M., Balmer, N.J. and Williams, A.M. (2002). The influence of crowd noise and experience upon refereeing decisions in football. Psychology of Sport and Exercise 3, 261-272. Ridder, G., Cramer, J.S. and Hopstaken, P. (1994). Down to ten: estimating the effect of a red card in soccer. Journal of the American Statistical Association 89, 1124-1127. Sutter, M. and Kocher, M.G. (2004). Favoritism of agents – the case of referees’ home bias. Journal of Economic Psychology 25, 461-469. Torgler, B. (2004). The economics of the FIFA football World Cup. Kyklos 57, 287-300. Witt, R. (2005). Do players react to anticipated sanction changes? Evidence from the English Premier League. Scottish Journal of Political Economy, forthcoming