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In this paper, we present a new application-focused benchmark dataset andresults from a set of baseline Natural Language Processing and Machine Learningmodels for prediction of match outcomes for games of football (soccer). Bydoing so we give a baseline for the prediction accuracy that can be achievedexploiting both statistical match data and contextual articles from humansports journalists. Our dataset is focuses on a representative time-period over6 seasons of the English Premier League, and includes newspaper match previewsfrom The Guardian. The models presented in this paper achieve an accuracy of63.18% showing a 6.9% boost on the traditional statistical methods.

Combining Machine Learning and Human Experts to Predict Match Outcomes in Football: A Baseline Model