Eigenvalues Make The Difference - A Network Analysis Of The Chinese Super League

To evaluate collective (macro) performance data in the Chinese Super League, social network analyses and graph theory were implemented in team sports performance analyses. For each team, we constructed a weighted and directed network in which nodes corresponded to players and arrows to passes. A total of 1200 matches during the 2014-2018 seasons were analysed. The results showed significant differences in general network measures among team competitive levels, match locations and match outcomes. Successful teams and home teams had significantly higher link, diameter, density and cluster coefficient values than did the unsuccessful teams or visiting teams; however, the winning teams had significantly lower density and cluster coefficient 2 values than did the losing teams. This study suggested that successful teams or teams with advantages (home, winner) have a high level of total passes and eigenvalues. This is the first report in which eigenvalues (the degree of a team's distribution of the ball during the match) were able to capture changes in dynamics between different teams. There were positive correlations between all the network variables and the total shots and no correlations between all the network variables and goals.