Player Classification Technique Based on Performance for a Soccer Team Using Machine Learning Algorithms

Abstract

The present scenario of Bangladesh Soccer Team is very much worrying. The absence of playing opportunities due to the miscoordination among the players has led the national team slip to their worst ever FIFA ranking of 194 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> . The ultimate success of a team depends upon its player selection. Generally, the coach and the management team select the best 11 players for each match from a pool of players by evaluating various attributes of the players. This paper aims to propose a player classification technique for selecting the best players automatically to form a soccer team. The players are classified whether they will play or not based on their performances using multiple machine learning algorithms. The results we achieved based on the performance attributes, we believe would help the coach and management team to build up a successful soccer team.