S-TRAINING brings together an inter-disciplinary group of experts in sports science, sports medicine and data science that works together to address various sports-data-related challenges. The general research approach in this network can be summarized as follows: we propose to develop innovative Data Science methods to address injury prevention and coordination/tactics/performance analyses from an inter-disciplinary perspective fuelled by expert knowledge in sports science and sports medicine. A particular strength of our network is the diversity of the datasets we will analyse, diversity in terms of sports, gender, athletes (professionals/amateurs) and heterogeneous data sources (obtained via modern data collection techniques such as wearables or Virtual Reality).
More concretely, our group pursues the following main goals:
Develop data-driven predictions for negative events in sports such as acute and chronic injuries or health complaints, and close knowledge gaps in injury aetiology by looking at potentially influencing factors such as technique, training regimen, psychological, biomechanical, performance-related and gender-specific aspects of the athletes.
Develop a computational understanding of optimised coordination for performance at two distinct levels: (i) coordination of limbs and joint motions of athletes to allow for high performances, and (ii) coordination of players of a team to allow for winning games.
By providing open access to the research solutions developed throughout the project, a large range of sport clubs and athletes (both professional and recreational), particularly in commercially weaker sports, will benefit from this research.
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