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Title: Forecasting football match outcomes with big data and bigger methods Authors:  Shixuan Wang - University of Reading (United Kingdom)
Luca De Angelis - University of Bologna (Italy)
Carl Singleton - University of Reading (United Kingdom)
James Reade - University of Reading (United Kingdom) [presenting]
Abstract: A range of methods are considered for forecasting outcomes of football matches. In particular, we apply big data, and econometrics methods designed to cope with a large range of explanatory variables (LASSO, general-to-specific) where possible to forecast outcomes. We evaluate methods using a range of betting-related strategies. We apply these methods to football matches across numerous leagues in Europe, including the big five Leagues of England, France, Germany, Italy, and Spain.