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
Group Members
Completed Projects
- Assessment and Improvement of Mental Health
- Digital Sports Bavaria
- miLife
- Digital Vision Trainer
- Digital Sports Hub
- Diagnostic Imaging in Virtual Reality
- Match data-based performance indicators in professional football
- ESI@Fitness
