Team movement analysis in football is critical in evaluating performance. The aim is to understand the underlying mechanics of group movement in football in relation with player physical performance measures. We have developed measures for team tempo which demonstrate correlation with team physical performance metrics (such as heart rates, work rates, and high intensity runs), match outcomes and seasonal KPIs.

 

The aim of this project is to comprehensively analyze team passing networks, identify large-scale principal network characteristics, and understand the significance of these network measures in elite level football. Our findings suggest a new set of measures to describe and characterize team passing in elite level football, as well as evaluate team performance, scout for talent and prepare for opposition.

 

We explore the use of hyper-networks in order to model player cliques formed during match play under various tactical formations. Manipulating parameters at different levels of the team, player selection is optimized to maximize ball passing & transmission, as well as productivity & chance creation, in an adaptable manner to suit the different tactical approaches of the team.

 

The aim of this project is to develop a model for football that considers the interplay of technical skill, tactical movement and athleticism. We explore the application of braid theory in order to integrate continuous movement data with discrete match event data, and derive metrics from the resulting model in a meaningful manner which practitioners can use directly to inform training sessions.