The duration of matches has been a common concern in professional tennis. Governing bodies have recently begun to introduce new match formats, like Fast4, to curb match lengths yet the impact of these formats on the professional game remains poorly understood. In this paper, we develop a shot-level Monte Carlo match simulation approach for estimating the duration, points played, and upset probability given a specific match format. Our model is built on validated models of the in-play and between-play time of matches using Hawk-eye tracking data and publicly available shot-level tennis statistics. When we applied our models to a variety of match formats with serve characteristics representative of current elite players, we found that Fast4 formats had an expected duration of 60 minutes, best of 3 averaged 90 minutes, and best of 5 averaged 120 minutes. Our results also showed that longer matches favor the better player and make match outcomes more predictable. Fast4 formats had a typical upset frequency of 20% compared to 13% for best of 3 matches and 10% for best of 5 matches. The modeling approach we have developed can be a useful resource for tennis governing bodies in assessing the impact of new match formats.
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