Fabian Wunderlich

Dr. Fabian Wunderlich is a Researcher at the German Sport University Cologne, working within the Institute for Training Science and Sports Informatics in the Department of Sports Informatics and Sports Game Research. His office is located in IG II, Room 115, and he can be contacted via email at f.wunderlich@dshs-koeln.de or by phone at +49 221 4982-4845. Previously, he completed his doctoral studies at the same institution.

Wunderlich's research focuses on the intersection of sports science and data analytics, with particular emphasis on football/soccer analysis. His work spans several key areas including sports forecasting, machine learning applications in sports, artificial data generation, and the analysis of gambling markets in sports contexts. His research fingerprint shows strong concentrations in forecasting (100%), sport (90%), gambling (44%), and artificial data (44%), reflecting his methodological approach to sports analytics.

Analysis of his recent publications reveals a consistent trend toward applying advanced data science techniques to sports performance analysis, particularly in football. His work frequently examines patterns in game events, player movements, and scoring opportunities using machine learning and statistical methods. A significant portion of his research investigates data sparsity issues in sports forecasting and develops methods to handle incomplete datasets through imputation and artificial data generation.

Wunderlich has been actively involved in multiple research projects, including 'Datenbasierte Ansätze zur Analyse von Fußballspielen aus der e-science Perspektive' (ongoing since 2020), 'How does spectator presence affect football?' (a funded project examining home advantage during the COVID-19 pandemic), and 'Nutzung von Big Data Analysen in Vorhersagemodellen im Sport' (2017-2022). His primary collaborator appears to be Daniel Memmert, with whom he has 29 joint publications and 4 joint projects.

His work has gained attention in academic circles with 12 readers on Mendeley for some publications and pickup by news outlets, particularly for research on Twitter data analysis during football matches and the effects of spectator presence on performance. Wunderlich's research demonstrates strong connections between theoretical data science approaches and practical applications in sports performance analysis.