  In this paper, we study collective interaction dynamics emerging in the game
of football-soccer. To do so, we surveyed a database containing body-sensors
traces measured during three professional football matches, where we observed
statistical patterns that we used to propose a stochastic model for the
players' motion in the field. The model, which is based on linear interactions,
captures in good approximation the spatiotemporal dynamics of a football team.
Our theoretical framework, therefore, becomes an effective analytical tool to
uncover the underlying cooperative mechanisms behind the complexity of football
plays. Moreover, we showed that it can provide handy theoretical support for
coaches to evaluate teams' and players' performances in competitive scenarios.
