Complex Network Analysis of Men Single ATP Tennis Matches
This work addresses questions about player evaluation and match prediction in tennis, which is incremental as it builds on existing network science methods for sports analysis.
The paper tackles the problem of evaluating player significance and fairness in ATP rankings by applying complex network analysis to men's singles tennis match data, and proposes a new predictive algorithm for forecasting match winners.
Who are the most significant players in the history of men tennis? Is the official ATP ranking system fair in evaluating players scores? Which players deserved the most contemplation looking at their match records? Which players have never faced yet and are likely to play against in the future? Those are just some of the questions developed in this paper supported by data updated at April 2018. In order to give an answer to the aforementioned questions, complex network science techniques have been applied to some representations of the network of men singles tennis matches. Additionally, a new predictive algorithm is proposed in order to forecast the winner of a match.