ABSTRACT
Based on a UEFA Champions League match between FC Bayern Munich and FC Barcelona, this chapter shows how positional data can be employed to analyze individual matches in both real time and post hoc. Positional data open up many new possibilities to model the tactical aspects of the game, find patterns, and create novel, advanced performance measures. For example, positional data contain information on players’ spatio-temporal formations on the field. In this chapter, neural networks are implemented to investigate formation types, perform interaction analyses of these two football heavyweights, and automatically detect actual tactical formations during the match. Besides the network approach, the Key Performance Indicator (KPI) pressing index is explained.
