SME: Learning Automata-Based Algorithm for Estimating the Mobility Model of Soccer Players

Soccer model and relation of players and coach has been analyzed by a learning automata-based method, called soccer mobility estimator (SME), who estimates the mobility model of soccer players. During a soccer match, players play according to a certain program designed by coach. The pattern of players´ mobility is not stochastic and it can be assumed that they are playing with a certain mobility model. Since knowledge about mobility model of nodes in mobile ad-hoc networks has a substantial effect on its performance evaluation, knowledge about mobility model of soccer players can be useful for coaches and experts for game analysis. In fact the mobility model of players could be an important parameter for assessment of team solidarity. Simulation results show that the mobility model of soccer players is similar, up to 66%, to the RPGM (reference point group mobility) mobility model.