Football Betting Research Articles

EFFICIENCY IN BETTING MARKETS: EVIDENCE FROM ENGLISH FOOTBALL

We analyze the efficiency of English football betting markets between 2002 and 2006. We find evidence of a positive favourite-longshot bias for both home odds and away odds. Draw odds are instead characterized by a negative longshot bias. We also identify a draw bias in the sense that betting at draw odds yields a higher return than betting at home or away odds. Finally, we investigate betting strategies that exploit the variance of odds between bookmakers.

Football Gambling Three Arm-Controlled Study: Gamblers, Amateurs and Laypersons

Background: Football (soccer) betting, as a strategic form of betting, became one of the favorite wagers for pathological gamblers. Previous studies demonstrated the psychological and biological significance of the ‘illusion of control’ (personal control) and ‘near miss’ results in gambling. In our study, we explored whether knowledge and expertise of pathological sports gamblers can ensure a successful bet. Sample and Methods: Participants were divided into three groups of individuals – pathological gamblers, amateurs and laypersons – and were asked to predict in advance the general result and the exact result of football matches in the European Champions League Round of 16. Results: The 165 participants included 53 pathological sports gamblers (52 males and 1 female), 78 laypersons (45 females and 33 males) and 34 amateurs (all males). After a thorough statistical analysis, we found no significant differences between the groups, no matter what kind of previous knowledge they had acquired. Conclusion: This study demonstrates that the ‘illusion of control’ of pathological gamblers, attained by knowledge of the game and its latest data and information (especially in a strategic gamble as football betting), has no factual background. Moreover, our study demonstrates without a doubt that there is no significant difference between the male pathological sports gamblers group and the male/female laypersons group.

Kelly's fractional staking updated for betting exchanges

In 1956, Kelly developed a staking system to calculate the optimal fraction of wealth to bet on each of a series of favourable bets. In line with historical betting markets, Kelly considered only back bets on events with a single favourable outcome. The recent advent of betting exchanges makes a much wider range of bets available. We extend Kelly's algorithm to betting on a single market, with both back and lay bets available, and we demonstrate the superiority of doing so with betting data collected during the 2009/2010 English Premiership season. We further show that a more general problem with multiple dependent markets can be described as linearly constrained convex optimization. As numerical solutions to these problems are nearly as advanced as those for linear systems, we argue that it is possible to consider this more general case to be solved (at least numerically). We demonstrate how it is possible to formulate such a problem in the case of football bets and we demonstrate the superior growth rate of such a strategy. Two further issues which Kelly did not have to consider are commission and the variability of market size. We modify the objective function which we have been maximizing to take account of commission and further improve the growth rate of wealth in our test data. We begin a discussion on market size, adding constraints to take account of it in our numerical solution and observe the effect. We note the level of wealth at which further growth is impeded by the market size.

Effects of expertise on football betting

BackgroundFootball (soccer) is one of the most popular sports in the world, including Europe. It is associated with important betting activities. A common belief, widely spread among those who participate in gambling activities, is that knowledge and expertise on football lead to better prediction skills for match outcomes. If unfounded, however, this belief should be considered as a form of “illusion of control.” The aim of this study was to examine whether football experts are better than nonexperts at predicting football match scores.MethodsTwo hundred and fifty-eight persons took part in the study: 21.3% as football experts, 54.3% as laypersons (non-initiated to football), and 24.4% as football amateurs. They predicted the scores of the first 10 matches of the 2008 UEFA European Football Championship. Logistic regressions were carried out to assess the link between the accuracy of the forecasted scores and the expertise of the participants (expert, amateur, layperson), controlling for age and gender.ResultsThe variables assessed did not predict the accuracy of scoring prognosis (R2 ranged from 1% to 6%).ConclusionsExpertise, age, and gender did not appear to have an impact on the accuracy of the football match prognoses. Therefore, the belief that football expertise improves betting skills is no more than a cognitive distortion called the “illusion of control.” Gamblers may benefit from psychological interventions that target the illusion of control related to their believed links between betting skills and football expertise. Public health policies may need to consider the phenomenon in order to prevent problem gambling related to football betting.

Baseball

Due to the use of sports wagering market data as a laboratory to test the Efficient Markets Hypothesis, sports bettors have been assumed to behave as investors. With the rejection of the balanced book hypothesis and the persistent support of market efficiency, the notion of the sports bettor as investor should be in doubt. Using betting volume data from online sportsbooks, bettors are shown to substitute out of baseball betting into football betting when the season starts. The authors argue that these findings are consistent with consumer behavior, but inconsistent with the notion of bettors as investors.

Dynamic Bayesian forecasting models of football match outcomes with estimation of the evolution variance parameter

Statistical models of football (soccer) match outcomes have potential applications to areas such as the development of team rankings and football betting markets. Much of the published work in this context has typically focused on the use of generalized linear models, which are non-dynamic in the sense that the parameters in the model, which often represent the underlying abilities of each team, are assumed to remain constant over time. Dynamic generalized linear models (DGLMs) on the other hand allow the abilities of each team to vary over time. This paper illustrates the application of a DGLM in the context of football match outcome prediction and describes improvements on similar work previously presented by the author, in relation to the estimation of a parameter in the model, referred to as the evolution variance, which is crucial in terms of optimizing the predictive performance of these types of models. Match results data from the Scottish Premier League from 2003/2004 to 2005/2006 are used to show that the DGLM approach provides improved predictive probabilities of future match outcomes compared to the non-dynamic form of the model. DGLMs are also Bayesian in terms of their structure and so a Bayesian approach to parameter estimation is required. This paper therefore illustrates a practical implementation of the DGLM model that can easily be deployed using the freely available software WinBUGS.

Regional information and market efficiency: the case of spread betting in United States college football

Using game results over a seven year span (1999–2006), we find that United States college football teams in arid regions “win” against the spread in 56.64% of games in which they host a team from a humid region. This result provides statistically significant evidence for both weak and strong form inefficiency in the spread betting markets of such games. By examining other cases of intraregional and interregional competition within the sport, we conclude that this inefficiency does not arise from the effects of travel or home field advantage. Rather, the result indicates that climate aridity is an observed characteristic for which college football betting markets do not accurately control. It is quite rare to find strong form market inefficiency arise from a single variable rather than from an elaborate, multivariable betting strategy. Therefore, the effect of climate aridity upon college football spread betting market efficiency can be characterized as dramatic. It is conjectured that remote market participants may need to “experience” certain types of relevant regional information, such as climate, to act in a market efficient manner.

How efficient is the European football betting market? Evidence from arbitrage and trading strategies

AbstractThis paper assesses the international efficiency of the European football betting market by examining the forecastability of match outcomes on the basis of the information contained in different sets of online and fixed odds quoted by six major bookmakers. The paper also investigates the profitability of strategies based on: combined betting, simple heuristic rules, regression models and prediction encompassing. The empirical results show that combined betting across different bookmakers can lead to limited but highly profitable arbitrage opportunities. Simple trading rules and betting strategies based on forecast encompassing are found capable of also producing significant positive returns. Despite the deregulation, globalization and increased competition in the betting industry over recent years, the predictabilities and profits reported in this paper are not fully consistent with weak‐form market efficiency. Copyright © 2008 John Wiley & Sons, Ltd.

College Football Rankings and Market Efficiency

The results in this article 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 that this is a fairly strong test of the efficiency of the college football betting market.

How Efficient is the European Football Betting Market? Evidence from Arbitrage and Trading Strategies

This paper assesses the international efficiency of the European football betting market by examining the forecastability of match outcomes on the basis of the information contained in online and fixed odds quoted by six major bookmakers. The paper also investigates the profitability of strategies based on: combined betting, simple heuristic rules, regression models and prediction encompassing. The empirical results show that combined betting across different bookmakers can lead to limited but highly profitable arbitrage opportunities. Simple trading rules and betting strategies based on forecast encompassing are found capable of also producing significant positive returns. Despite the deregulation, globalization and increased competition in the betting industry over recent years, these predictabilities and profits are not fully consistent with weak-form market efficiency.

Efficiency of football betting markets: the economic significance of trading strategies

Prior studies of the Australian Rugby League betting market report a degree of predictability well in excess of that attributable to chance. However, two important recent changes in the structure of the market facilitate an unambiguous assessment of the statistical significance of predictability and the economic significance of returns to betting strategies. The present paper reexamines the efficiency of the Australian Rugby League betting market under the revised market structure. In addition, a set of measures of the economic significance of trading strategies are developed and implemented. Relative to prior studies, the out-of-sample success of the predictive model has diminished notably under the revised market structure; although a naive strategy betting on home underdogs still performs significantly better than can be attributed to chance. Simulation experiments suggest that the documented level of predictability from several strategies generates economically significant returns.

In search of the source of informed trader information in the college football betting market

The movement between the opening and closing of betting lines on sports events has been shown to contain valuable information. The purpose of this study is to search for the source of this valuable information. Changes in college football betting lines are examined with respect to information from the widely disseminated Dunkel Index, the Associated Press Writers’ Poll, and lagged performance variables. It is found that bettors use this information to bet but that this information is not significant to betting outcomes, which indicates noise trading. Most importantly, it is shown that the unexplained betting line movements are most important in explaining final game outcomes. This result leads to the conclusion that informed bettors are using private information.

Identifying Investor Sentiment from Price Paths: The Case of Football Betting

Identifying Investor Sentiment from Price Paths: The Case of Football Betting

The Favourite‐Longshot Bias and Market Efficiency in UK Football betting

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.

Identifying Investor Sentiment from Price Paths: The Case of Football Betting

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. Copyright 1999 by University of Chicago Press.

Modelling Association Football Scores and Inefficiencies in the Football Betting Market

SUMMARY 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.

Football Betting and the Efficient Market Hypothesis

Three betting rules which had been nonrandomly profitable in both their initial application to the 1969–74 National Football League seasons and their replication during the years of 1975–81 were applied to all NFL games played between September 1984 and January 1994. One rule proved to be nonrandom and profitable for a third consecutive trial—a feat suggesting that bettors may be able to “beat the bookie” and, more broadly, that prices in competitive markets may not discount all available information in swift fashion.

A generalized model for testing the home and favorite team advantage in point spread markets

Most sports teams play as either the favorite or the underdog and either at home or away. The failure to recognize the symmetric and interdependent relations between these characteristics has led previous researchers to use potentially biased methods to test for rationality and efficiency in football betting markets and thus to reach inappropriate conclusions. We develop a more general specification, which also incorporates ‘pick-em’ games and games played on neutral sites, and find little or no evidence against market efficiency in the NFL and college betting markets for regular season games. We do, however, uncover evidence of biased betting lines for Superbowls.

The Efficiency of Australian Football Betting Markets

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 in‐sample and out‐of‐sample, we offer a number of reasons why we are cautious about interpreting these results as conclusive evidence of market inefficiency.

Do bettors prefer long shots because they are risk-lovers, or are they just overconfident?

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.