June 18, 2010
AND SO IT BEGINS... (via The Other Brother)
Quantifying the Performance of Individual Players in a Team Activity (Jordi Duch1,2,3, Joshua S. Waitzman1, Luís A. Nunes Amaral1,2,4*, 1 Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois, United States of America, 2 Northwestern Institute on Complex Systems, Northwestern University, Evanston, Illinois, United States of America, 3 Department of Computer Science and Mathematics, Universitat Rovira i Virgili, Tarragona, Spain, 4 Howard Hughes Medical Institute, Northwestern University, Evanston, Illinois, United States of America, PLoS ONE)
BackgroundPosted by Orrin Judd at June 18, 2010 5:39 AMTeamwork is a fundamental aspect of many human activities, from business to art and from sports to science. Recent research suggest that team work is of crucial importance to cutting-edge scientific research, but little is known about how teamwork leads to greater creativity. Indeed, for many team activities, it is not even clear how to assign credit to individual team members. Remarkably, at least in the context of sports, there is usually a broad consensus on who are the top performers and on what qualifies as an outstanding performance.
Methodology/Principal FindingsIn order to determine how individual features can be quantified, and as a test bed for other team-based human activities, we analyze the performance of players in the European Cup 2008 soccer tournament. We develop a network approach that provides a powerful quantification of the contributions of individual players and of overall team performance. [...]
Soccer is widely viewed as the most popular sport world-wide. Soccer is also one of the most difficult sports to analyze quantitatively due to the complexity of the play and to the nearly uninterrupted flow of the ball during the match. Indeed, unlike baseball or basketball, for which there is a wealth of statistical performance data detailing how each player contributes to the final result, in soccer it is not trivial to define quantitative measures of an individual's contribution. Moreover, because soccer scores tend to be low, simple statistics such as number of assists, number of shots or number of goals only rarely provide a reliable measure of a player's true impact on the match's outcome. Instead, the real measure of the performance of a player is “hidden” in the plays of a team: a player can have tremendous impact by winning the ball from the other team or by passing to a teammate who then makes an assist.
Similarly to many other team activities, this type of information required to quantify in detail the role of a team member on team performance is not usually gathered and analyzed in a systematic way (for exceptions see [7], [8]). In the case of soccer, while the assignment of the credit is usually purely based on the subjective views of commentators and spectators, there typically exists a strong consensus on the quality of team play or of individual performances.
Methods Top
The Euro Cup tournament is second only to the World Cup in terms of general interest, attracting millions of spectators and widespread media coverage. The 2008 tournament was unusual in the amount of statistical information that was collected and published online (see http://euro2008.uefa.com). This wealth of information enabled us to develop a new approach to quantify the performance of players and teams inspired by methods from social network analysis [9], [10].
To capture the influence of a given player on a match, we construct a directed network of “ball flow” among the players of a team. In this network, nodes represent players and arcs are weighted according to the number of passes successfully completed between two players. We also incorporate shooting information by including two non-player nodes, “shots to goal” and “shots wide”. A player's node is connected to these two nodes by arcs weighted according to the number of shots. We refer to the resulting networks as “flow networks”, and we build networks for the two teams in every match of the tournament.
In order to obtain performance information, we start with the observation that a soccer team moves the ball with the opponent's goal in mind, keeping possession and shooting when the opportunity arises. A player's passing accuracy, which represents the fraction of passes initiated by a player that reach a teammate, and his shooting accuracy, which accounts for the fraction of shots that do not miss the goal, describe the capability of a player to move the ball towards the opponent's goal (Figs. 1A and 1B).