Soccer has been difficult to break into statistics, but researchers devise a way to objectively rank players.
Few points can be counted in soccer to determine strong players.
New software uses various data to quantify players' performances by generalizing social network analysis.
The technique calculates connections between players in a network and in making a goal.
Objective criteria now can be used to determine just who are the best footballers on the pitch, thanks to a U.S. researcher who developed a computer model to quantify players' performance, new research out Wednesday found.
"In soccer, there are relatively few big things that can be counted," explained Luis Amaral, a professor of chemical and biological engineering at Northwestern University, lead author of the paper in the online edition of PloS One.
"You can count how many goals someone scores, but if a player scores two goals in a match, that's amazing. You can really only divide two or three goals or two or three assists among, potentially, eleven players," added the Portuguese-American scientist.
"Most of the players will have nothing to quantify their performance at the end of the match," he said.
To try to bridge this statistical gap, unlike clearer data from other sports such as basketball and baseball, Josh Waitzman of Northwestern developed software able to objectively rank all the statistics from all matches in the 2008 European Cup.
Then Luis Amaral and Jordi Duch, an assistant professor of applied mathematics and computer science at Universitat Rovira I Virgili in Spain, used the data to quantify players' performance by generalizing methods from social network analysis.
"You can define a network in which the elements of the network are your players," Amaral said. "Then you have connections between the players if they make passes from one to another. Also, because their goal is to score, you can include another element in this network, which is the goal."
Amaral's data squad mapped out the flow of the ball between players in the network as well as shooting stats, and analyzed the results.
"We looked at the way in which the ball can travel and finish on a shot," said Amaral, who also is a member of the Northwestern Institute on Complex Systems (NICO) and an Early Career Scientist with the Howard Hughes Medical Institute.
"The more ways a team has for a ball to travel and finish on a shot, the better that team is. And, the more times the ball goes through a given player to finish in a shot, the better that player performed."
Amaral insists: "It would never happen by chance that we would get such striking agreement with the consensus opinion of so many experts if our measure wasn't good."