Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceThe overall goal for the current study is to present a literature review of analytics, precisely machine
learning (ML) reference authors in terms of methods and applicable scopes of study, in football
where is a field that historically there are empirical decisions and the usage of analytics has been
growing intensely. The research aims to list relevant academic contributions published between 2010
and 2020, performing a comparable picture per authors across the following subsets: player
individual technical skills and team performance. Furthermore, the approach will provide a summary
of studies for machine learning methods applied in football.
Such outcomes of this study would contribute to the discussion about football analytics. Regarding
that these summaries can drive researchers to have a deep dive into the fields of interest straight to
references preview studied in the thesis. Results indicate that football analytics has broadly vast
opportunities in terms of research, regarding machine learning methods and a high potential to have
a deep exploration of team and player perspective. This study can leverage and pavement new
further in-depth and targeted investigation toward football analytics
