论文标题
结合机器学习和人类专家以预测足球比赛中的匹配结果：基线模型
Combining Machine Learning and Human Experts to Predict Match Outcomes in Football: A Baseline Model
论文作者
论文摘要
在本文中，我们提出了一个新的以应用程序为重点的基准数据集，并从一组基线自然语言处理和机器学习模型中产生，以预测足球比赛的匹配结果（足球）。通过这样做，我们为预测准确性提供了基准，可以利用人类体育记者的统计匹配数据和上下文文章来实现。我们的数据集专注于在英超联赛的6个赛季中的代表性时期，其中包括《卫报》的报纸比赛预览。本文介绍的模型的准确性为63.18％，显示传统统计方法的增长6.9％。
In this paper, we present a new application-focused benchmark dataset and results from a set of baseline Natural Language Processing and Machine Learning models for prediction of match outcomes for games of football (soccer). By doing so we give a baseline for the prediction accuracy that can be achieved exploiting both statistical match data and contextual articles from human sports journalists. Our dataset is focuses on a representative time-period over 6 seasons of the English Premier League, and includes newspaper match previews from The Guardian. The models presented in this paper achieve an accuracy of 63.18% showing a 6.9% boost on the traditional statistical methods.
