The topic of this research is the quantitative and qualitative analysis of the state of professional men's singles tennis from 2018 to 2020 using techniques for social and complex network analysis, as well as statistical methods. The network of all tennis players was modeled based on their mutual encounters for each individual year and for all observed years together, including the ego networks of the Big Three players: Roger Federer, Rafael Nadal, and Novak Djokovic. Within the tennis player network, players represent the nodes of the network, and a connection between two nodes is established if two players have encountered each other in a tournament. The tennis player network was modeled for each year separately, as well as an aggregated network for all years. The Python programming language (using the NetworkX library) was used for the analysis of the modeled social network. The processing of the primary dataset was performed by writing appropriate scripts in Python. The network visualization was accomplished using the Gephi tool.