This project brings together methodological competence in statistics, machine learning and computer science with current developments in sport sciences as well as technological progress in wearables and medical diagnostics in order to optimize training load of top athletes in endurance sports. We collect and process „big data“ from training and performance processes of individual athletes and use state-of-the-art machine learning technology in order to measure effective training load, to predict the effect of training impulses and to optimize training management. It is carried out as a pilot project in cooperation with the Austrian Rowing Federation and is tailored to the specific needs and conditions in rowing. In a later stage, the insights gained from the project will be transferred to disciplines with similar training contents and requirements, such as swimming, triathlon, cycling, cross-country skiing and long/mid-distance running.

The project brings together researchers from statistics, computer science, mathematics, sports science and sports medicine. While being practically highly relevant in order to strengthen the competitiveness of Austrian top-level sports, the project will be scientifically challenging and will produce novel insights and findings. The project is funded by the Bundesministeriums für Kunst, Kultur, öffentlichen Dienst und Sport and is carried out by the Research Network Data Science and the Institute of Sports Science of the University of Vienna in collaboration with the Austrian Rowing Federation.