65 citations · 104 across the 6 of their papers we have counts for
6 papers
Model quality in football: Quantifying the quality of an Expected Threat model
Koen van Arem, Jakob Söhl, Mirjam Bruinsma +1
The recent growth in data availability in football has increased the risk of incorrect use of data-driven models, making guidelines on their validation and application necessary. T…
Forecasting the future development in quality and value of professional football players
Koen W. van Arem, Floris Goes-Smit, Jakob Söhl
Transfers in professional football (soccer) are risky investments because of the large transfer fees and high risks involved. Although data-driven models can be used to improve tra…
Testing for no effect in regression problems: a permutation approach
Michał Ciszewski, Jakob Söhl, Ton Leenen +2
Often the question arises whether can be predicted based on using a certain model. Especially for highly flexible models such as neural networks one may ask whether a seemi…
Improving state estimation through projection post-processing for activity recognition with application to football
Michał Ciszewski, Jakob Söhl, Geurt Jongbloed
The past decade has seen an increased interest in human activity recognition based on sensor data. Most often, the sensor data come unannotated, creating the need for fast labellin…
Bernstein -- von Mises theorems for statistical inverse problems II: Compound Poisson processes
Richard Nickl, Jakob Söhl
We study nonparametric Bayesian statistical inference for the parameters governing a pure jump process of the form where is a st…
Nonparametric Bayesian posterior contraction rates for discretely observed scalar diffusions
Richard Nickl, Jakob Söhl
We consider nonparametric Bayesian inference in a reflected diffusion model with discretely sampled observations . We ana…