Rouven Michels (M.Sc.)

Research associate (PhD student)

Room: V9-126
Phone: +49 521 106-5103
E-mail: r.michels@uni-bielefeld.de

Since 10/2020: PhD student in the Statistics and Data Analysis Group
05/2019-09/2020: Associate at KPMG (Corporate Governance Services – Risk Management)
10/2013-02/2019: Studies of Mathematical Economics (B.Sc. & M.Sc.) at Bielefeld University

Michels, R., Ötting, M., Langrock, R. (2023)
"Bettors' reaction to match dynamics: Evidence from in-game betting"
European Journal of Operational Research, in press

"Using tensor product B-splines for nonparametric inference in multivariate hidden Markov models", IMS International Conference on Statistics and Data Science, Florence, Italy, December 2022
"Extending the Dixon and Coles model: an application to women’s football data", Workshop of the Centre for Statistics, Bielefeld, November 2022
"Do bettors value actions on the pitch?", 9th MathSport International, Reading, UK, July 2022
"Using tensor product B-splines for nonparametric inference in multivariate hidden Markov models", DAGStat, Hamburg, March 2022
"Using tensor product B-splines for nonparametric inference in multivariate hidden Markov models", Workshop of the Centre for Statistics, Bielefeld, March 2022
"Patterns of betting behaviour for news in live betting markets", 12th ESEA Conference on Sport Economics (held online), August 2021
"Using state-space models for investigating time-varying team strengths in a live betting market", 9th Young Researchers Workshop of the Centre for Statistics, Bielefeld, July 2021
"Investigating drivers of stakes in a football live betting market", 8th MathSport International (held online), Reading, UK, June 2021 (video available at https://youtu.be/G5Rzxffj4_M)
"The Reaction to News in Live Betting", Statistics Seminar Series (held online), Bielefeld, April 2021

Practicals for the lecture ''Generalised linear models'', winter term 2021/22
Tutorials for the lecture courses "Stochastik I" and "Stochastik II" (2015–2019)

Statistics and Data Analysis Group