Modelling Association Football (Soccer) Results Using the Wisdom of Crowds

“Football is round” is a commonly mentioned cliché that describes the fickle nature of the game. However, the high level of randomness doesn’t seem to stop statisticians and econometricians from attempting to model and predict game results. Peeters (2014) demonstrates that models utilizing crowds-assessed player “market” valuations as inputs can produce a fairly good performance in modelling football game results. In this paper, I attempt to improve his baseline model by further implementing the information of matchday line-ups and player position. Even though the additional information doesn’t seem to improve model performance, the new models are still able to yield accurate predictionsi. Meanwhile, some interesting patterns regarding (national) team structure and player valuation are revealed during the research.