Estimation of Influential Parameter Using Gravitational Search Optimization Algorithm for Soccer

摘要

Competitive sport has one phenomenal or fundamental aspect of selecting players into playing squad for a game that can influence a Club or a team in almost all major aspects. Various Characteristics or behavioral aspects of players will be instrumental towards the selection of a specific player into a team depending on the nature, level, or type of completion the club or team participates in. Many parameters such as medical, physical, technical and, Psychological aspects of players make the task of mangers or coach a herculean to select 15 players out of 30 or 40 players available in his squad for a particular season. The role of managers or coaches is significantly challenging looking into the aspects most desirable towards the optimal contribution of players. Hence the parameters which are considered highly influential towards a Club or team cannot be analyzed manually due to various constraints such as time, the volume of players, or the limitation of human errors in decision making. The primary objective of this paper is towards assisting managers or coaches to see through this by applying Sports Parameter Estimation Gravitational Search Algorithm (SPEGSA) towards analytical ability in player selection considering minimal errors and time constraints using a stochastic approach. This paper gives an overview of how soft computing techniques help in optimization of selection procedures of team players for the matches to be played and competed in a soccer league for a given team at different levels of competition by measuring various influential parameters recorded at different point of juncture for every player in a team and estimating the parameter using the subset of evolutionary computation techniques and metaheuristic optimization algorithm.