Prof. Dr.

Wrobel, Stefan

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  • Publication
    Constructing Spaces and Times for Tactical Analysis in Football
    ( 2021)
    Andrienko, Gennady
    ;
    Andrienko, Natalia
    ;
    Anzer, Gabriel
    ;
    Bauer, Pascal
    ;
    Budziak, Guido
    ;
    Fuchs, Georg
    ;
    Hecker, Dirk
    ;
    Weber, Hendrik
    ;
    Wrobel, Stefan
    A possible objective in analyzing trajectories of multiple simultaneously moving objects, such as football players during a game, is to extract and understand the general patterns of coordinated movement in different classes of situations as they develop. For achieving this objective, we propose an approach that includes a combination of query techniques for flexible selection of episodes of situation development, a method for dynamic aggregation of data from selected groups of episodes, and a data structure for representing the aggregates that enables their exploration and use in further analysis. The aggregation, which is meant to abstract general movement patterns, involves construction of new time-homomorphic reference systems owing to iterative application of aggregation operators to a sequence of data selections. As similar patterns may occur at different spatial locations, we also propose constructing new spatial reference systems for aligning and matching movements irrespective of their absolute locations. The approach was tested in application to tracking data from two Bundesliga games of the 2018/2019 season. It enabled detection of interesting and meaningful general patterns of team behaviors in three classes of situations defined by football experts. The experts found the approach and the underlying concepts worth implementing in tools for football analysts.
  • Publication
    A conceptual framework and taxonomy of techniques for analyzing movement
    ( 2011)
    Andrienko, Gennady
    ;
    Andrienko, Natalia
    ;
    Bak, Peter
    ;
    Keim, Daniel A.
    ;
    Kisilevich, S.
    ;
    Wrobel, Stefan
    Movement data link together space, time, and objects positioned in space and time. They hold valuable and multifaceted information about moving objects, properties of space and time as well as events and processes occurring in space and time. We present a conceptual framework that describes in a systematic and comprehensive way the possible types of information that can be extracted from movement data and on this basis defines the respective types of analytical tasks. Tasks are distinguished according to the type of information they target and according to the level of analysis, which may be elementary (i.e. addressing specific elements of a set) or synoptic (i.e. addressing a set or subsets). We also present a taxonomy of generic analytic techniques, in which the types of tasks are linked to the corresponding classes of techniques that can support fulfilling them. We include techniques from several research fields: visualization and visual analytics, geographic informa tion science, database technology, and data mining. We expect the taxonomy to be valuable for analysts and researchers. Analysts will receive guidance in choosing suitable analytic techniques for their data and tasks. Researchers will learn what approaches exist in different fields and compare or relate them to the approaches they are going to undertake.