No abstract

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.

The objective of the study was to compare goal scoring patterns among the “Big Five” European football leagues during the 2009/2010–2018/2019 seasons. A total of 18 pattern dimensions related to the offense pattern, the shooting situation and the scoring time period were evaluated. Kruskal–Wallis analyses revealed significant pattern differences among the five leagues. The Spanish La Liga showed a greater proportion of goals from throw-ins. The English Premier League had a higher tendency to score from corner kicks. The German Bundesliga had the greatest number of goals from counterattacks and indirect free kicks, and the Italian Serie A had the greatest proportion of penalties. Ligue 1’s scoring ability is weaker than that of the other leagues, especially Bundesliga. The Bundesliga had an overwhelming advantage in goals scored on big chances with assists, while the Premier League had an advantage in goals scored with assists that were not from big chances. However, the differences among the five leagues in the mean goals scored in the last 15 min and the goals from elaborate attacks and direct free kicks were not statistically significant. These results provide a valuable addition to the knowledge of different goal patterns of each league and allow us to better understand the differences among the leagues.