We investigate the state-of-the-art in score-based soccer match outcome modelling to identify the top-performing methods across diverse classes of existing approaches to the problem. Namely, we bring together various statistical methods based on Poisson and Weibull distributions and several general ranking algorithms (Elo, Steph ratings, Gaussian-OD ratings) as well as domain-specific rating systems (Berrar ratings, pi-ratings). We review, reimplement and experimentally compare these diverse competitors altogether on the largest database of soccer results available to identify true leaders. Our results reveal that the individual predictions, as well as the overall performances, are very similar across the top models tested, likely suggesting the limits of this generic approach to score-based match outcome modelling. No study of a similar scale has previously been done.

中文翻译：

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四十年基于分数的足球比赛结果预测：实验回顾

我们研究了基于得分的足球比赛结果建模的最新技术，以确定解决该问题的各种现有方法中表现最佳的方法。即，我们汇集了基于泊松和威布尔分布的各种统计方法和几种通用排名算法（Elo、Steph 评级、Gaussian-OD 评级）以及特定领域的评级系统（Berrar 评级、pi-ratings）。我们在最大的足球结果数据库中对这些不同的竞争对手进行审查、重新实施和实验性比较，以识别真正的领导者。我们的结果表明，在测试的顶级模型中，个人预测以及整体表现非常相似，这可能表明这种基于分数的匹配结果建模的通用方法存在局限性。