Complex Network Analysis of Men Single ATP Tennis Matches

TL;DR

This paper applies complex network analysis to men's ATP tennis matches to identify key players, evaluate ranking fairness, and predict match outcomes, offering new insights into player significance and future match possibilities.

Contribution

It introduces a novel application of complex network science to analyze ATP tennis data and proposes a new predictive algorithm for match outcome forecasting.

Findings

Identifies the most significant players in men's tennis history.

Assesses the fairness of ATP ranking system.

Develops a new algorithm to predict match winners.

Abstract

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.