A data analytics approach to player assessment

Abstract

There is abundance of data in the new digital age which can be harnessed to gather insights through application of data analytics. This study develops model to assess the performance and thereby forecast ranking of players through data available in public domain at The Fédération Internationale de Football Association. The study applies Principal Component Analysis followed by classification. A combination of these two approaches seeks to determine ranking of players and to classify them in different categories. Results indicate that player ranks can be predicted and classified on their playing attributes and accordingly an appropriate selection decision can be made.