A Flexible Approach to Football Analytics: Assessment, Modeling and Implementation
Quantitative analysis in football is difficult due to the complexity and continuous fluidity of the game. Even though there is an increased accessibility of spatio-temporal data, scientific approaches to extract valuable information are seldomly useful in practice. We propose a new approach to building an information system for football. This approach consists of a method to extract football-specific concepts from interviews, to formalize them in a performance model, and to define and implement the data structures and algorithms in StreamTeam, a framework for the detection of complex (team) events. In this paper we present this approach in detail and provide an example for its use.
KeywordsFootball Modeling Event detection Spatio-temporal data
This work has been partly supported by the Hasler Foundation in the context of the project StreamTeam, contract no. 16074.
- 4.Fernandez, J., Bornn, L.: Wide open spaces: a statistical technique for measuring space creation in professional soccer. In: MIT Sloan Sports Analytics Conference (2018)Google Scholar
- 5.Kuckartz, U.: Qualitative Inhaltsanalyse. Methoden, Praxis, Computerunterstützung, 4 edn. Beltz Verlagsgruppe, Weinheim (2018)Google Scholar
- 9.Probst, L., Al Kabary, I., Lobo, R., Rauschenbach, F., Schuldt, H., Seidenschwarz, P., Rumo, M.: SportSense: user interface for sketch-based spatio-temporal team sports video scene retrieval. In: Proceedings of the 1st Workshop on User Interface for Spatial and Temporal Data Analysis, Tokyo, Japan. CEUR-WS (2018)Google Scholar
- 10.Probst, L., Brix, F., Schuldt, H., Rumo, M.: Real-time football analysis with StreamTeam. In: Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems, Barcelona, Spain, pp. 319–322. ACM (2017). https://doi.org/10.1145/3093742.3095089
- 11.Probst, L., Rauschenbach, F., Schuldt, H., Seidenschwarz, P., Rumo, M.: Integrated real-time data stream analysis and sketch-based video retrieval in team sports. In: Proceedings of the 2018 IEEE International Conference on Big Data, pp. 548–555. IEEE (2018). https://doi.org/10.1109/BigData.2018.8622592
- 12.Spearman, W.: Beyond expected goals. In: MIT Sloan Sports Analytics Conference (2018)Google Scholar