In the world of sport, team cohesion is a topic that is heavily researched by scholars. What makes a team successful? What do teams need from their players to be the top performers? This all depends on the context and theory that is able to explain intended results from the reserch. Social Network Analysis (SNA) is a methodology just beginning to explore the aspect of what makes a cohesive team. When visualizing a network, there are different ways to measure how individual actors and relationships within a network interact as a unit. A lot of these questions about what makes a successful team is answered by the amount of team cohesion is present. There is theory to explain that the more a team works together and trusts each other the more optimal their performance will be.
SNA is a tool that can help examine team cohesion at both the individual and the group level. It can be used to examine the various relationships within the group. Since we know performance and cohesion are highly correlated, SNA can be used as an explanatory tool in seeking to understand the relational embeddedness and connectedness on the individual levels of a team. When looking at the centrality of a node within a network we are trying to examine the prominence of important nodes and the number of connections a node has to other nodes. One way to measure degree centrality is by its “closeness” to other nodes. This can be measured by either the in-degree (prominence of nodes) or out-degree (influential nodes) within a network. Another measurement of node centrality is “betweenness”, this is the extent to which a node is connected to other nodes. And lastly “eigenvector” centrality of a node is its connection to other important nodes.
One article by Warner, Bowers, and Dixon (2012) used SNA to examine the concept of team cohesion among a basketball team. The researchers used in-degree centrality (prominence of nodes) to look at the density (visualize team cohesion). They were also able to use SNA longitudinally by measuring team cohesion links (efficacy, friendship, trust etc.) at four different times during a team’s season and watch the density (team cohesion) change over time. Depicted below you will notice from the off-season (top) to post-season (bottom) we can visually see the team became more cohesive by its density and indegree measures of the individual actors.
In contrast to how players connect by links of intangible factors, Trequattrini, Lombardi, and Battista (2015) looked at tangible factors of actual soccer passes between players during a soccer game in relation to team performance. Like the other article, these scholars used density to examine team relations. The picture below demonstrates as an example how relationships (passes) between players of a team which can used in a different way to examine team cohesion during an on-field performances.
Both of these articles of great examples of how theory and past literature can drive different perspectives in analyzing similar networks. Each article used different links among their players to look at how cohesive the team operated as a unit. SNA has a lot of potential in understanding how the networks of players effect cohesion and group dynamics among the sporting world!
Trequattrini, R., Lombardi, R., & Battista, M. (2015). Network analysis and football team performance: a first application. Team Performance Management, 21(1/2), 85-110.
Warner, S., Bowerts, M. T., & Dixon, M. A. (2012). Team dynamics: a social network perspective. Journal of Sport Management, 26, 53-66.