Soccer generates fewer performance statistics than does a sport such as baseball. A network analysis approach enables researchers to guage the value of individual players.

That’s a shout World Cup enthusiasts don’t hear too frequently. Soccer’s known for low-scoring games, which makes it difficult to find an objective means of measuring the skill of top players. In a given game, a couple might nail a goal or have an assist. But who’s the best of the best?

This conundrum plagued Luis Amaral as a kid in Portugal. Now, a professor of biology and chemical engineering at Northwestern, he used his team’s computational skills to find the best. The work is in the journal Public Library of Science One. Graduate student Josh Waitzman wrote software using data from the 2008 Euro Cup website. They mapped the flow of the ball among players. They evaluated the ways the ball can travel. And they were able to rank players based on how many times and ways the ball passed through them to finish a given shot.

Their rankings match the opinions of coaches and experts. For example, all agree that Spain’s Xavi is a great player. Amaral and Waitzman say this network model could be also used for non-soccer tasks, such as evaluating teammates on a group work project. (Announcer’s call of “ANNUAL REPORT!”)