Sports Analytics

The Sports Analytics group applies different methods in the fields of Machine Learning, Wearables and Human-Computer Interaction to analyze and predict the performance of athletes. For gaining deeper insights into the behavior of athletes in specific sports like running, soccer or volleyball, we conduct in-the-wild and lab studies using inertial measurement units (IMUs), motion capture systems and extended realities. The group also utilizes extended realities to simulate training scenarios and applies them to various fields of application like therapy or performance improvement. Our research contributes to the development of more precise analysis tools in sports and thus makes the assessment and training of athletes more efficient. This can lead to an increase in performance, but also help to recognize harmful movement patterns for the prevention of injuries.

Research areas: Experimental Studies, Human-Computer Interaction, Machine Learning, Signal Processing, Wearables


Group Head

Dr.-Ing. Eva Dorschky

Room: Room 01.024


Group Members


Running Projects


Completed Projects