Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Andrienko, G., Andrienko, N., Budziak, G., Dykes, J., Fuchs, G., von Landesberger, T., Weber, H.: Visual analysis of pressure in football. Data Min. Knowl. Discov. 31(6), 1793–1839 (2017). https://doi.org/10.1007/s10618-017-0513-2
Drust, B., Green, M.: Science and football: evaluating the influence of science on performance. J. Sport. Sci. 31(13), 1377–1382 (2013). https://doi.org/10.1080/02640414.2013.828544
Duch, J., Waitzman, J.S., Amaral, L.A.N.: Quantifying the performance of individual players in a team activity. PLoS ONE 5(6), e10,937 (2010). https://doi.org/10.1371/journal.pone.0010937
Fernandez, J., Bornn, L.: Wide open spaces: a statistical technique for measuring space creation in professional soccer. In: MIT Sloan Sports Analytics Conference (2018)
Kuckartz, U.: Qualitative Inhaltsanalyse. Methoden, Praxis, Computerunterstützung, 4 edn. Beltz Verlagsgruppe, Weinheim (2018)
Link, D., Hoernig, M.: Individual ball possession in soccer. PLoS ONE 12(7), e0179,953 (2017). https://doi.org/10.1371/journal.pone.0179953
Mackenzie, R., Cushion, C.: Performance analysis in football: a critical review and implications for future research. J. Sport. Sci. 31(6), 639–676 (2013). https://doi.org/10.1080/02640414.2012.746720
Noghabi, S.A., Paramasivam, K., Pan, Y., Ramesh, N., Bringhurst, J., Gupta, I., Campbell, R.H.: Samza: stateful scalable stream processing at LinkedIn. Proc. VLDB Endow. 10(12), 1634–1645 (2017). https://doi.org/10.14778/3137765.3137770
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)
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
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
Spearman, W.: Beyond expected goals. In: MIT Sloan Sports Analytics Conference (2018)
Acknowledgements
This work has been partly supported by the Hasler Foundation in the context of the project StreamTeam, contract no. 16074.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Seidenschwarz, P., Rumo, M., Probst, L., Schuldt, H. (2020). A Flexible Approach to Football Analytics: Assessment, Modeling and Implementation. In: Lames, M., Danilov, A., Timme, E., Vassilevski, Y. (eds) Proceedings of the 12th International Symposium on Computer Science in Sport (IACSS 2019). IACSS 2019. Advances in Intelligent Systems and Computing, vol 1028. Springer, Cham. https://doi.org/10.1007/978-3-030-35048-2_3
Download citation
DOI: https://doi.org/10.1007/978-3-030-35048-2_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-35047-5
Online ISBN: 978-3-030-35048-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)