This paper examines the performance of five different measures for forecasting men’s and women’s professional tennis matches. We use data derived from every match played at the 2018 and 2019 Wimbledon tennis championships, the 2019 French Open, the 2019 US Open, and the 2020 Australian Open. We look at the betting odds, the official tennis rankings, the standard Elo ratings, surface-specific Elo ratings, and weighted composites of these ratings, including and excluding the betting odds. The performance indicators used are prediction accuracy, calibration, model discrimination, Brier score, and expected return. We find that the betting odds perform relatively well across these tournaments, while standard Elo (especially for women’s tennis) and surface-adjusted Elo (especially for men’s tennis) also perform well on a range of indicators. For all but the hard-court surfaces, a forecasting model which incorporates the betting odds tends also to perform well on some indicators. We find that the official ranking system proved to be a relatively poor measure of likely performance compared to betting odds and Elo-related methods. Our results add weight to the case for a wider use of Elo-based approaches within sports forecasting, as well as arguably within the player rankings methodologies.

中文翻译：

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基于Elo的收视率如何预测职业网球比赛？

本文研究了五种不同的预测男子和女子职业网球比赛的测量方法的性能。我们使用从2018年和2019年温布尔登网球锦标赛，2019年法国公开赛，2019年美国公开赛和2020年澳大利亚公开赛所进行的每场比赛获得的数据。我们查看投注赔率，官方网球排名，标准Elo评分，特定于表面的Elo评分以及这些评分的加权综合，包括但不包括投注赔率。所使用的性能指标是预测准确性，校准，模型判别，布里尔得分和预期回报。我们发现，在这些赛事中，下注赔率的表现相对较好，而标准Elo（尤其是女子网球）和经过表面调整的Elo（尤其是男子网球）在一系列指标上也表现良好。对于除硬地赛道以外的所有赛道，结合了赔率的预测模型在某些指标上也表现良好。我们发现，与投注赔率和Elo相关方法相比，官方排名系统被证明是对可能表现的相对较差的度量。我们的结果增加了在体育预测以及运动员排名方法中广泛使用基于Elo的方法的理由。