Introduction

Abstract

The digital transformation is one of the major challenges of our time (Bounfour, 2016; Castells, 1996). On a smaller scale, this also affects the world of sport, where the ongoing digitalization and developments in the field of sensor technology have led to a rapid increase in the volume of data. In particular, spatio-temporal position data, which are now available almost everywhere in soccer, harbor huge potential for performance analysis. However, these vast amounts of data have little value in themselves. Rather, the challenge is to develop new methods of data analysis, and to use the resulting structures and correlations in sports data to augment and enhance our knowledge about sport.