DIXON, M.J. and S.G. COLES, 1997. Modelling Association Football Scores and Inefficiencies in the Football Betting Market. Applied Statistics. [Cited by 42] (4.70/year)
Abstract: "A parametric model is developed and fitted to English league and cup football data from 1992 to 1995. The model is motivated by an aim to exploit potential inefficiencies in the association football betting market, and this is examined using bookmakers' odds from 1995 to 1996. The technique is based on a Poisson regression model but is complicated by the data structure and the dynamic nature of teams' performances. Maximum likelihood estimates are shown to be computationally obtainable, and the model is shown to have a positive return when used as the basis of a betting strategy."
ANDERSSON, P., M. EKMAN and J. EDMAN, 2003. Forecasting the fast and frugal way: A study of performance and information-processing strategies of experts and non-experts when predicting the World Cup 2002 in soccer. Unpublished manuscript, Center for Economic Psychology, …. [Cited by 2] (0.68/year)
Abstract: "This paper investigates forecasting performance and judgmental processes of experts and nonexperts in soccer. Two circumstances motivated the paper: (i) little is known about how accurately experts predict sports events, and (ii) recent research on human judgment suggests that ignorance-based decision-strategies may be reliable. About 250 participants with different levels of knowledge of soccer took part in a survey and predicted the outcome of the first round of World Cup 2002. It was found that the participating experts (i.e., sport journalists, soccer fans, and soccer coaches) were not more accurate than the non-experts. Experts overestimated their performance and were overconfident. While the experts claimed to have relied on analytical approaches and much information, participants with limited knowledge stated that their forecasts were based upon recognition and few pieces of information. The paper concludes that a recognition-based strategy seems to be appropriate to use when forecasting worldwide soccer events."
DEBNATH, S., et al., 2002. Characterizing Efficiency and Information Incorporation in Sports Betting Markets. Proceedings of the Ninth Research Symposium on Emerging …. [Cited by 1] (0.25/year)
Abstract: "We analyze data from thirty-three “interactive” sports betting markets on the World Sports Exchange (WSEX), where betting is allowed continuously throughout a sporting event. Our study includes markets based on soccer (European football) games from the 2002 World Cup, and markets based on basketball games from the 2002 National Basketball Association (NBA) championship in the United States. We show that prices in such betting markets on average approach the correct outcome over time. We record important events throughout the course of the games, for example changes in score. We show that the corresponding price dynamics in the markets are closely coupled with actual game events: the market reacts almost instantaneously to the occurrence of those events, indicating agreement with the assumptions of the efficient markets hypothesis. We compare the dynamics of price changes in soccer games with dynamics in basketball games, highlighting the characteristic differences between these two types of games and their corresponding markets. We also compare the nature of these sports betting markets with “political stock markets” (betting markets on the outcomes of political elections) on the Iowa Electronic Market (IEM)."
GOLEC, J. and M. TAMARKIN, 1991. The degree of inefficiency in the football betting market, Journal of Financial Economics, 30(2), 311-323. 318. [Cited by 33] (2.21/year)
Abstract: "This paper tests the hypothesis that the football betting market is efficient. Our statistical tests are stronger than those in previous studies, and we examine both NFL and college data over a sample period of fifteen years. Our statistical tests detect two specific biases in the NFL market and an unspecified bias in the college market. We examine the year-to-year consistency and magnitudes of the biases and find that the NFL bias against home teams has been nearly eliminated, while the bias against underdogs has increased. Profitable exploitation of the biases depends upon transaction costs."
AVERY, C. and J. CHEVALIER, 1999. Identifying Investor Sentiment from Price Paths: The Case of Football Betting. Journal of Business. [Cited by 27] (3.89/year)
Abstract: "We examine the hypothesis that sentimental bettors can affect the path of prices in football betting markets. We hypothesize that sentimental traders follow the advice of false experts, believe excessively in momentum strategies, bet excessively on teams that are well known and covered in the media. We generate proxies for these sources of sentiment and show that point spreads move predictably over the course of the week, partially in response to variables known prior to the opening of betting. We show that a betting strategy of betting against the predicted movement in the point spread is borderline profitable."
BADARINATHI, R. and L. KOCHMAN, 1996. Football Betting and the Efficient Market Hypothesis.. American Economist. [Cited by 7] (0.70/year)
Abstract: "The efficient market hypothesis asserts that investors cannot consistently "beat the market" because stocks reside in perpetual equilibrium. Supporters point to the 100,000+ analysts and traders whose collective actions ensure that the prices of the 3000 or so major stocks do not stray too far from their respective values. Pankoff (1968) reasoned that the football-betting market attracts participants no less numerous, knowledgeable or competitive than its Wall Street counterpart and therefore functions as a convenient proxy for testing the fallibility of market consensus."
CAIN, M., D. LAW and D. PEEL, 2000. The Favourite-Longshot Bias and Market Efficiency in UK Football betting. Scottish Journal of Political Economy, Volume 47 Page 25 - February 2000. [Cited by 4] (0.67/year)
Abstract: "It is shown that the individual fixed-odds betting market on UK football exhibits the same favourite-longshot bias as that found in horse-racing. The bias appears both in betting on results (home win, away win or draw) and in betting on specific scores, and there are certain trading rules which appear to be profitable. Poisson and Negative Binomial regressions are carried out to estimate the mean number of goals scored by a team in a match with given market odds for the various outcomes. Tables of odds for individual scores are derived and these appear to fit the actual outcomes far better than those of the bookmaker."
SHARPE, G., 1997. Gambling on Goals: A Century of Football Betting. Mainstream Publishing Company, Ltd. [Cited by 4] (0.45/year)
BRAILSFORD, T.J., et al., 1995. The Efficiency of Australian Football Betting Markets. Australian Journal of Management. [Cited by 3] (0.27/year)
Abstract: "This paper examines the efficiency of the two major Australian football betting markets: the Australian Rugby League (ARL) FootyTAB market and the Australian Football League (AFL) Footywin market. Probit and ordered probit models are tailored to the unique structures of the markets. This circumvents some potential econometric problems, and also allows us to test betting strategies in which a bet is placed only when there is a high ex-ante probability of success. Our probit models are successful in predicting game outcomes in both the ARL and AFL. While several of our betting strategies generate significant profits, both insample and out-of-sample, we offer a number of reasons why we are cautious about interpreting these results as conclusive evidence of market inefficiency."
STERN, H., 1991. On the Probability of Winning a Football Game, The American Statistician, Vol. 45, No. 3. (Aug., 1991), pp. 179-183. [Cited by 19] (1.27/year)
Abstract: "Based on the results of the 1981, 1983, and 1984 National Football League seasons, the distribution of the margin of victory over the point spread (defined as the number of points scored by the favorite minus the number of points scored by the underdog minus the point spread) is not significantly different from the normal distribution with mean zero and standard deviation slightly less than fourteen points. The probability that a team favored by p points wins the game can be computed from a table of the standard normal distribution. This result is applied to estimate the probability distribution of the number of games won by a team. A simulation is used to estimate the probability that a team qualifies for the championship playoffs."
HARVILLE, D., 1980. Predictions for National Football League Games Via Linear-Model Methodology. Journal of the American Statistical Association, 75, 516--524. [Cited by 20] (0.77/year)
Abstract: "Results on mixed linear models were used to develop a procedure for predicting the outcomes of National Football League games. The predictions are based on the differences in score from past games. The underlying model for each difference in score takes into account the home-field advantage and the difference in the yearly characteristic performance levels of the two teams. Each team's yearly characteristic performance levels are assumed to follow a first-order autoregressive process. The predictions for 1,320 games played between 1971 and 1977 had an average absolute error of 10.68, compared with 10.49 for bookmaker predictions."
GOLEC, J.G. and M.G. TAMARKIN, 1995. Do bettors prefer long shots because they are risk-lovers, or are they just overconfident?. Journal of Risk and Uncertainty. [Cited by 7] (0.64/year)
Abstract: This study examines whether bettors' risk preferences or overconfidence in choosing winners better explains their well documented preference for low-probability wagers. Although previous studies using racetrack data often suggest that risk-loving behavior explains long-shot preference, such data cannot distinguish between the alternative explanations. We use football betting data to make the comparison and find that overconfidence more closely fits the data. This result complements evidence of overconfidence from behavioral studies as well as stock-market models of overconfident noise traders."
DIXON, M.J. and M.E. ROBINSON, 1998. A Birth Process Model for Association Football Matches, The Statistician. [Cited by 20] (2.52/year)
Abstract: "Data from over 4000 recent association football (soccer) matches from the main English competitions show clear evidence that the rate of scoring goals changes over the course of a match. This rate tends to increase over the game but is also influenced by the current score. We develop a model for a soccer match that incorporates parameters for both the attacking and the defensive strength of a team, home advantage, the current score and the time left to play. This model treats the number of goals scored by the two teams as interacting birth processes and shows a satisfactory fit to the data. We also investigate football cliches and find evidence that contradicts the cliche that a team is more vulnerable just after it has scored a goal. Our model has applications in the football spread betting market, where prices are updated during a match, and may be useful to both bookmakers and bettors."
POPE, P.F. and D.A. PEEL, 1989. Information, Prices and Efficiency in a Fixed-Odds Betting Market. Economica. [Cited by 15] (0.89/year)
Abstract: "This paper examines the efficiency of the Association Football betting market in the United Kingdom. The notable features of this market are that the odds are fixed some time before matches occur and differ between bookmaking firms. While there is some evidence of ex post inefficiency, there does not appear to be profitable betting strategies that could have been implemented ex ante during the sample period."
DIXON, M.J. and P.F. POPE, 2003. The Value of Statistical Forecasts in the UK Association Football Betting Market, International Journal of Forecasting, Volume 20, Issue 4, October-December 2004, Pages 697-711 [Cited by 2] (0.68/year)
Abstract: "In this paper, we evaluate the economic significance of statistical forecasts of UK Association Football match outcomes in relation to betting market prices. We present a detailed comparison of odds set by different bookmakers in relation to forecast model predictions, and analyse the potential for arbitrage across firms. We also examine extreme odds biases. A detailed re-examination of match result odds and a new examination of correct score odds for the period 1993 to 1996 suggest that the market is inefficient."
DIXON, M.J. and P.F. POPE, 1996. Inefficiency and bias in the UK association football betting market. Unpublished working paper). Lancaster, UK: University of …. [Cited by 2] (0.20/year)
GODDARD, J. and I. ASIMAKOPOULOS, 2004. Forecasting football results and the efficiency of fixed-odds betting. Journal of Forecasting. [Cited by 6] (3.10/year)
Abstract: "An ordered probit regression model estimated using 10 years' data is used to forecast English league football match results. As well as past match results data, the significance of the match for end-of-season league outcomes, the involvement of the teams in cup competition and the geographical distance between the two teams' home towns all contribute to the forecasting model's performance. The model is used to test the weak-form efficiency of prices in the fixed-odds betting market. A strategy of selecting end-of-season bets with a favourable expected return according to the model appears capable of generating a positive return."
DIXON, M.J. and P. POPE, 1996. Inefficiency and bias in the UK football betting market. Submitted to Mangmnt Sci. [Cited by 1] (0.10/year)
FORREST, D., R. SIMMONS and J. GODDARD, 2005. Odds setters as forecasting: the case of the football betting market. International Journal of Forecasting, vol 21(3), pp 552-564. [Cited by 1] (1.07/year)
OSBORNE, E., 2001. Efficient Markets? Don't Bet on It. Journal of Sports Economics. [Cited by 5] (1.01/year)
Abstract: "This article tests the efficient-markets hypothesis by looking at profits in National Football League (NFL) betting markets. The author tests whether successful betting strategies exist when points scored and allowed earlier in a season can outperform the betting line in predicting the margin of victory in NFL games and finds that profitable strategies exist. In addition, the author finds that over the course of a season, bettors do imperfectly incorporate information about team strength and that NFL victory margins are a highly variable process."
CROWDER, M., et al., Dynamic modelling and prediction of English Football League matches for betting. ingentaconnect.com. [Cited by 3] (?/year)
"We focus on modelling the 92 soccer teams in the English Football Association League over the years 1992–1997 using refinements of the independent Poisson model of Dixon and Coles. Our framework assumes that each team has attack and defence strengths that evolve through time (rather than remaining constant) according to some unobserved bivariate stochastic process. Estimation of the teams' attack and defence capabilities is undertaken via a novel approach involving an approximation that is computationally convenient and fast. The results of this approximation compare very favourably with results obtained through the Dixon and Coles approach. We note that the full model (i.e. the model before the above approximation is made) may be implemented using Markov chain Monte Carlo procedures, and that this approach is vastly more computationally expensive. We focus on the probabilities of home win, draw or away win because these outcomes constitute the primary betting market. These probabilities are estimated for games played between any two of the 92 teams and the predictions are compared with the actual results."
FAIR, R.C. and J.F. OSTER, 2003. College Football Rankings and Market Efficiency.“. Unpublished paper. http://fairmodel. econ. yale. edu/rayfair …. [Cited by 1] (0.34/year)
Abstract: "The results in this paper show that various college football ranking systems have useful independent information for predicting the outcomes of games. Optimal weights for the systems are estimated, and the use of these weights produces a predictive system that is more accurate than any of the individual systems. The results also provide a fairly precise estimate of the size of the home field advantage. These results may be of interest to the Bowl Championship Series in choosing which teams to play in the national championship game. The results also show, however, that none of the systems, including the optimal combination, contains any useful information that is not in the final Las Vegas point spread. It is argued in the paper that this is a fairly strong test of the efficiency of the college football betting market."
SCHMIDT, C. and A. WERWATZ, 2002. How accurate do markets predict the outcome of an event? the Euro 2000 soccer championships …. Max planck Institute for Research into Economic Systems …. [Cited by 6] (1.52/year)
Abstract: "For the Euro 2000 Soccer Championships an experimental asset market was conducted, with traders buying and selling contracts on the winners of individual matches. Market-generated probabilities are compared to professional bet quotas, and factors that are responsible for the quality of the market prognosis are identified. The comparison shows, that the market is more accurate than the random predictor and slightly better than professional bet quotas, in the sense of mean square error. Moreover, the more certain the market predicts the outcome of an event the more accurate is the prediction."