Books

Use Historical Odds to Predict the Final Result of Sports Events.


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Predictions

Predicting sports events from past results

by Douwe Buursma

Towards effective betting on football matches. A system for predicting the results of football matches that beats the bookmakers’ odds is presented. The predictions for the matches are based on previous results of the teams involved.

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Predictions

Modelling football match results and the efficiency of fixed-odds betting

by John Goddard, Ioannis Asimakopoulos

An ordered probit regression model estimated using 15 years’ data is used to model English league football match results. As well as past match results data, the significance of the match for end-ofseason league outcomes; the involvement of the teams in cup competition; the geographical distance between the two teams’ home towns; and the average attendances of the two teams all contribute to the model’s performance. The model is used to test the weak-form efficiency of prices in the fixedodds betting market, and betting strategies with a positive expected return are identified.

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Predictions

Using bookmaker odds to predict the final result of football matches

by Karol Odachowski, Jacek Grekow

There are many online bookmakers that allow betting money in virtually every field of sports, from football to chess. The vast majority of online bookmakers operate based on standard principles and establish the odds for sporting events. These odds constantly change due to bets placed by gamblers. The amount of changes is associated with the amount of money bet on a given odd. The purpose of this paper was to investigate the possibility of predicting how upcoming football matches will end based on changes in bookmaker odds. A number of different classifiers that predict the final result of a football match were developed. The results obtained confirm that the knowledge of a group of people about football matches gathered in the form of bookmaker odds can be successfully used for predicting the final result.

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Predictions

Statistical data analytics of football for beating the odds

by Luca Airoldi

The aim of this project is to analyse the past 20 years of football data about the Italian Serie A league in order to gain an insight understanding of statistical facts and patterns for football outcome predictions for the sport betting industry. There have been a number of research papers and books written in the past about football matches results in relation to the efficiency of fixed odd betting, exploring a number of techniques such as Fuzzy Models and Neural Networks.

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Predictions

Numerical Algorithms for Predicting Sports Results

by Jack David Blundell

Numerical models can help predict the outcome of sporting events. The features within these models rely on data associated with the competitors. Here, a logistic regression model was used to predict the outcome of American Football matches. As well as using data such as the two teams’ previous results, novel features such as stadia size and the distance the away team had to travel were incorporated. This model was seen to perform better than two baselines: (i) simply predicting the home team or (ii) using the previous result between the teams. By adding more informative features to the model, a prediction accuracy of 65% was produced. These predictions matched that of bookmakers showing that the information enclosed within the model could be used to predict games to a highly successful rate.

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Predictions

A statistical development of fixed odds betting rules in soccer

by Ian Milliner, Paul White and Don J. Webber

Two simple but seemingly profitable betting rules for betting on the away win in association football are developed. One rule is consistent with avoiding those games in which there is a clear favourite. The second rule is based directly on modelling bookmaker odds and assessing the residuals under the fitted model. Contrary to previous research the betting rule using the residuals suggests avoiding betting on those games where there are large discrepancies between bookmaker odds and predicted-model odds.

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Predictions

Beating the bookie: A look at statistical models for prediction of football matches

by Helge Langseth

In this paper we look at statistical models for predicting the outcome of football matches in a league. That is, our aim is to find a statistical model which, based on the game-history so far in a season, can predict the outcome of next round’s matches. Many such models exist, but we are not aware of a thorough comparison of the models’ merits as betting models. In this paper we look at some classical models, extract their key ingredients, and use those as a basis to propose a new model. The different models are compared by simulating bets being made on matches in the English Premier League.

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Predictions

Winners and losers in soccer World Cup: A study of recent history and how to bet if you must

by Fragiskos Archontakis

Football betting in Europe has seen a rapid growth in the last two decades. However, the betting market seems to be rather inert in becoming an efficient market in a similar fashion as inefficiencies have been appearing in the international financial markets. A typical fixed odds set provided by the bookmaker for the result of a soccer match would be: (odds for home team win, odds for draw, odds for away team win).

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