ABSTRACT
What are potential trends in sports analysis in the future is the guiding question of this chapter. To this end, four different venues are investigated. An obvious development well under way already and will continue to do so is the increasing use of tracking data across sports disciplines. Accordingly, potentials and possible limitations of future tracking data are discussed. Tied to data tracking is the increasing demand for greater contextualization of sports analysis data. As more and more detailed data are gathered, gaining insights into individual performance and more specific contexts will be increasingly possible. To help coping with these more complex data, analysis techniques from machine learning will become more important in the future. Thus, a short primer on possible applications of machine learning techniques discusses how these techniques might help future sports analysts. The chapter ends with a topic still in its infancy, the development of theoretical models of sports data. At present, analyses mostly use an ad-hoc approach lacking an overarching and guiding theoretical framework. Yet, this lack counterintuitively hampers the adoption of sports analysis techniques in practical settings and what possible routes for future developments are available are the closing topics of this chapter.
