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Predicting probabilities for the 2010 FIFA World Cup games using a Poisson-Gamma model

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In this paper, we provide probabilistic predictions for soccer games of the 2010 FIFA World Cup modelling the number of goals scored in a game by each team. We use a Poisson distribution for the number of goals for each team in a game, where the scoring rate is considered unknown. We use a Gamma distribution for the scoring rate and the Gamma parameters are chosen using historical data and difference among teams defined by a strength factor for each team. The strength factor is a measure of discrimination among the national teams obtained from their memberships to fuzzy clusters. The clusters are obtained with the use of the Fuzzy C-means algorithm applied to a vector of variables, most of them available on the official FIFA website. Static and dynamic models were used to predict the World Cup outcomes and the performance of our predictions was evaluated using two comparison methods.
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Keywords: Bayesian inference; Fuzzy C-means clustering; Poisson-Gamma distribution; World Cup predictions; dynamic model

Document Type: Research Article

Affiliations: Department of Statistics, Fluminense Federal University, Niteroi, RJ, Brazil

Publication date: July 1, 2013

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