Results Of Football Matches Research Articles

The value of statistical forecasts in the UK association football betting market

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.

Forecasting football results and the efficiency of fixed‐odds betting

AbstractAn 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. Copyright © 2004 John Wiley & Sons, Ltd.

Forecasting sport: the behaviour and performance of football tipsters

Professional advice is available in several forecasting contexts, such as share prices, sales and the weather. English newspaper tipsters offer professional advice on the outcomes of English and Scottish football (soccer) matches. Such advice could potentially inform selections of bettors in fixed odds or pools betting. This paper investigates the effectiveness of the guidance given by newspaper tipsters. Employing a sample of three tipsters and 1694 English league games, we find that tipster success rates are higher than would follow from random forecasting methods. We identify some differences between the processes by which actual results and tipster forecasts are determined. Likelihood-ratio tests imply that the tipsters fail adequately to utilise easily obtainable public information on teams’ strength. Further tests show that only one of three tipsters appears to make successful use of other unspecified information relevant to game outcomes. A consensus forecast across the three tipsters appears to outperform any single tipster.

Attendance demand: an investigation of repeat fixtures

Using fixed betting odds for football match outcomes this paper improves on previous versions of outcome uncertainty models of attendance demand by utilizing data on ‘repeat’ fixtures between two teams. This provides some control over the variation in match characteristics which influence demand. The analysis of ‘repeat’ fixtures also enables an improved treatment of the ‘core support’ element of attendances. The contribution of fixed betting odds in explaining attendance demand is confirmed as is the ‘U’–shaped relationship between attendance and home team probability of success.

Computer Forecasting of Australian Rules Football for a Daily Newspaper

An exponential smoothing technique operating on the margins of victory was used to predict the results of Australian Rules football matches for a Melbourne daily newspaper from 1981-86 and again for a competitor in 1991-92. An initial ‘quick and dirty’ program used only a factor for team ability and a common home ground advantage to predict winning margins. Probabilities of winning were accumulated to predict a final ladder, with a simulation to predict chances of teams finishing in any position. Changes to the competition forced a more complicated approach, and the current version uses several parameters which allow for ability, team/ground interaction, team interaction, and a tendency for team ability to regress towards the mean between seasons. A power method is used to place greater weight on the errors in closer matches, and errors across the win-lose boundary. While simple methods were used originally, the Hooke and Jeeves method was used in optimizing the parameters of the current model. Both the original model and the improved version performed at the level of expert tipsters.

Computer Forecasting of Australian Rules Football for a Daily Newspaper

An exponential smoothing technique operating on the margins of victory was used to predict the results of Australian Rules football matches for a Melbourne daily newspaper from 1981-86 and again for a competitor in 1991-92. An initial ‘quick and dirty’ program used only a factor for team ability and a common home ground advantage to predict winning margins. Probabilities of winning were accumulated to predict a final ladder, with a simulation to predict chances of teams finishing in any position. Changes to the competition forced a more complicated approach, and the current version uses several parameters which allow for ability, team/ground interaction, team interaction, and a tendency for team ability to regress towards the mean between seasons. A power method is used to place greater weight on the errors in closer matches, and errors across the win-lose boundary. While simple methods were used originally, the Hooke and Jeeves method was used in optimizing the parameters of the current model. Both the original model and the improved version performed at the level of expert tipsters.

Voetbalprognoses

SummaryFootball poolsA main point in the discussions of whether the Dutch football pools are in defiance of the law is the problem of skill in prediction. It is said that experts on football have a greater chance to win prices in the pool than other participants and in this respect the pool differs from a lottery. The author makes an analysis of the scores of the prognoses of football journalists, under the assumption that these journalists are experts in predicting the results of football matches. He finds that journalists, if participating, would never have won a price in a pool and that mechanically applied non‐expert methods of forecasting yield predictions which are not much worse than the scores of the supposed experts.