Big data analytics: Using big data analytics in tracking player performance and scouting in football

In an era characterized by emerging tech and digital transformation, the sports industry is leveraging big data analytics which has given rise to fields like sport an-alytics (SA). In the game of football (soccer), the exponential rise in available data has led to lots of innovation and research on how data can be maximized in performance anal-ysis, scouting, injury prevention, management etc. This research provides of overview knowledge into big data analytics in sports with emphasis in football while paying attention to player performance tracking and scouting. Scouting is reliant on player performance tracking and as such a data driven decision approach will be beneficial in a system still dominated by bilateral relations and intuitive comments of scouting teams. A model is presented in this research for tracking performance, rating and rec-ommending players using data acquired. The data consist of five national European competitions in the 2017/2018, Euro 2016 and 2018 World cup. The data was used with permission from Luca Papalardo et al as it was first used in his research paper "A public data set of spatio-temporal match events in soccer competitions."