Balance in Competition in Dutch Soccer

Koning, Ruud H.

doi:10.1111/1467-9884.00244

Cited by 144 publications

(113 citation statements)

References 11 publications

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“…Similarly, Szymanski (2003) identifies three kinds of uncertainty: match uncertainty, season uncertainty, and championship uncertainty. Koning (2000) points out that the quality of the play in absolute games and uncertainty of the outcomes are the two main reasons for interest in a particular football contest. The outcome and quality of the game are the goods that is sold to the public.…”

Section: A Brief Review Of the Competitive Balance Concept In Footballmentioning

confidence: 99%

Research on the Prediction of the likely Winners of the Euro 2008 Football Tournament

Halıcıoğlu¹

2009

Journal of Quantitative Analysis in Sports

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The objective of this research is to provide a statistical measurement to predict the likely winners of international football tournaments with particular reference to the Euro 2008 football tournament. This research argues that there exists a positive relationship between the competitive balance and success in international football tournaments. The level of the competitive balance in a domestic football league is measured by the seasonal coefficients of variation (CV) of the end-of-season points. The CV values are employed as ranking indicators between the contesting countries in international football tournaments to predict the likely winners. The seasonal CV values are computed from the top divison football leagues of participating countries of Euro 1996, Euro 2000, Euro 2004, and Euro 2008 order to rank and to predict the likely winner of these tournaments. The results indicate that the higher the level of domestic competition the better chance of winning an international football tournament. The CV ranking is also compared to UEFA ranking and to the odds of some well known bookmakers in predicting the likely winners of the Euro 2008 football tournament. On the basis of the overall results, this research predicts that the likely winners of the Euro 2008 football tournament would be France, Spain or Germany.

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Section: A Brief Review Of the Competitive Balance Concept In Footballmentioning

confidence: 99%

Research on the Prediction of the likely Winners of the Euro 2008 Football Tournament

Halıcıoğlu¹

2009

Journal of Quantitative Analysis in Sports

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“…As a result, researchers continue to introduce a variety of football models which are formulated by diverse forecast methodologies. While some of these focus on predicting tournament outcomes (Kuonen, 1996;Buchner, et al, 1997;Koning et al, 2003;Halicioglu, 2005a;Halicioglu, 2005b) or league positions (Koning, 2000), our interest is in predicting outcomes of individual matches.…”

Section: Introductionmentioning

confidence: 99%

pi-football: A Bayesian network model for forecasting Association Football match outcomes

Constantinou

Fenton

Neil

2012

Knowledge-Based Systems

116

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A Bayesian network is a graphical probabilistic belief network that represents the conditional dependencies among uncertain variables, which can be both objective and subjective. We present a Bayesian network model for forecasting Association Football matches in which the subjective variables represent the factors that are important for prediction but which historical data fails to capture. The model (pi-football) was used to generate forecasts about the outcomes of the English Premier League (EPL) matches during season 2010/11 (but is easily extended to any football league). Forecasts were published online at www.pi-football.com prior to the start of each match. In this paper, we demonstrate that a) using an appropriate measure of forecast accuracy, the subjective information improved the model such that posterior forecasts were on par with bookmakers' performance; b) using a standard profitability measure with discrepancy levels at ≥ 5%, the model generates profit under maximum, mean, and common bookmakers' odds, even allowing for the bookmakers' built-in profit margin.Hence, compared with other published football forecast models, pi-football not only appears to be exceptionally accurate, but it can also be used to 'beat the bookies'.

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“…A second type of model assumes just one fitness parameter for each team and the outcome (home win, draw, away win) is then predicted after comparing the difference of the team fitness parameters with some fixed parameters [13]. The model parameters are then estimated based on the results of the whole season.…”

Section: Introductionmentioning

confidence: 99%