November 15, 2012

Basketball teams offer insights into building strategic networks

Posted: November 15, 2012
Phoenix Suns 2010 playoff series
Interactions between members of NBA basketball teams provide a research opportunity for strategic network analysis. This Phoenix Suns photo was taken during the 2010 NBA playoff series.
Photo by: Phoenix Suns: Barry Gossage
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Weighted graph of ball transitions
This is a weighted graph of ball transitions across two games for the (a) Bulls, (b) Cavaliers, (c) Celtics and (d) Lakers. Red edges represent transition probabilities. Player nodes are sorted by decreasing degrees clockwise from the left. The thicker the red line, the more frequently that pass occurs during play.
Photo by: School of Life Sciences
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Weighted graph of Phoenix Suns ball transitions
Weighted graph of the Phoenix Suns ball transitions. The thicker the red line, the more frequently that pass occurs during play.
Photo by: School of Life Sciences
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What started out as a project to teach undergraduate students about network analysis, turned into an in-depth study of whether it was possible to analyze a National Basketball Association (NBA) basketball team’s strategic interactions as a network. Arizona State University researchers discovered it is possible to quantify both a team’s cohesion and communication structure.

The researchers’ findings appear in an online November issue of PLOS ONE.

Jennifer Fewell, a professor in ASU’s School of Life Sciences in the College of Liberal Arts and Sciences, and lead investigator on the project, explains that because teams are an integral part of both human and animal societies – understanding how a team’s interactions as a whole affect its success or failure is important.

“We were able to come up with a hypothesis about strategy and then apply network analysis to that,” says Fewell. “Often, people simply create networks and then conduct descriptive analysis of them, but they don’t actually explain why they would expect an individual in a group to communicate the way they do. We take a different approach by suggesting that there are potentially successful ways to organize your team if you use this strategy then we should expect this network metric to show up as an indicator – sort of a proof of concept.”

The researchers measured two offensive strategies to learn whether differences in offensive strategy could be determined by network properties. First, they looked at whether teams moved the ball to their shooting specialists — measured as “uphill/downhill flux,” and second, whether they passed the ball in an unpredictable way — measured as team entropy. They analyzed games from the first round of playoffs in the 2010 season and gathered an extensive amount of data on 16 teams.

To evaluate the teams as networks, researchers graphed player positions and ball movement among players, as well as shots taken. Then, they used that data to find out whether network metrics can measure team decisions in a useful way. The study involved more than 1,000 ball movements and 100 ball sequences.

“What that paper basically says is that for the 2010 NBA playoffs the most successful teams were the ones that used a less predictable, more distributed offense and that connected their players more,” said Fewell. “Those were the teams that had actually hired more elite players and allowed them to work together.”

Fewell believes measuring team cohesion and communication is important.

“It’s one way to capture the essence of a team,” Fewell explained. “You work in teams for all different kinds of reasons. The fundamental idea of needing cohesion and communication structure among the individuals and the team is critical and it’s not easily quantified – and this gives you a way to quantify it.”

You may be wondering how the Phoenix Suns measured up.“I started working on this in part because I’m a Suns fan, especially of the ‘run and gun’ Suns,” shared Fewell. “Our data suggested though that the 2010 Suns played the game as a fairly traditional point-guard centered play style. The Lakers and Celtics, in contrast, showed the network equivalent of the triangle offense, and it paid off for them.  They were the teams in the finals that year.”

The study included researchers from ASU’s School of Life Sciences, School of Mathematical and Statistical Sciences, and Center for Social Dynamics and Complexity.

The paper is published on the PLOS ONE website: http://dx.plos.org/10.1371/journal.pone.0047445%20

Sandy Leander, sandra.leander@asu.edu
480-965-9865
School of Life Sciences