Abstract
The goal of this study was to present an accurate and rapid detection system to identify patterns in tennis, based on t-pattern analysis. As a case study, the break point situations in the final matches of the clay court tournaments played during the seasons 2011 and 2012 between the tennis players Novak Djokovic and Rafael Nadal were chosen. The results show that Nadal achieves a higher conversion rate with respect to Djokovic in the break point situations, independent of the outcome of the match. Some repetitive patterns of both players were revealed in break point circumstances. In long rally sequences (higher than seven hits), the Spanish player won more break points, both serving and receiving, as a result of unforced errors of his opponent's backhand. In medium rally sequences (between four and seven hits), other factors such as the type, direction or serve location have shown to play an important role in the outcome of the point. The study also reveals that Djokovic frequently commits double faults in these critical situations of the match. This is the first time that t-patterns have been used to analyze the sport of tennis. The technique is based on computer vision algorithms and video recording material to detect particular relationships between events and helps to discover the hidden mechanistic sequences of tennis players.