Institute of Sports Science

Talent Identification and Development in Football

As part of a larger research program on talent identification and development in football, this project within the Data Science and Sports Lab focusses on the application of machine learning techniques and Bayesian modelling (dynamic latent variable approaches) for the prediction of future success based on complex data gained from talent assessments. In a first study, we evaluate the utility of machine learning techniques (e.g., neural networks, boosting methods, and support vector machines) for examining prognostic validity of speed abilities and technical skills in youth elite football.

Research Line: Athletes, Teams and Performance

Funding / Support: German Football Association (Deutscher Fußball-Bund e.V.)

Project Team: Oliver Höner, Augustin Kelava, Pascal Kilian, Daniel Leyhr