Diving into data driven match analysis in football with floodlight and open data - Bassek, M.; Memmert, D.; Rein, R. (15. Symposium der dvs-Sektion "Sportinformatik und Sporttechnologie": Zwischen Geistesakrobatik und praktischer Anwendung: Innovationen in der Sportinformatik und Sporttechnologie - Abstractband, 2024)
Introduction The analysis of position and event data for match analysis in football has seen an increasing interest in research and practice in recent years (Memmert, 2022, 2023). However, the barriers to enter this field can be high for newcomers. Sports scientists are often not trained programmers but (especially position-) data require complex parsing, filtering and manipulation routines before further analysis. These are often incompatible across data providers. Another reason is the limited public availability of high-quality data. No data set of synchronized event- and position data from elite football matches exists to this day. We tackle these challenges by introducing the software package floodlight (Raabe et al., 2022) for Python along with making seven matches of professional football available under open source.