floodlight - A high-level, data-driven sports analyticsframework

Abstract

The increase of available data has had a positive impact on the entire sports domain and especially sport science Two major data sources of relevance in this domain are spatiotemporal tracking data of athlete positions as well as manually annotated match event data These two data types are regularly collected by professional sport organizations in different team invasion games such as football, basketball, or handball These data sources open up a whole range of new analysis possibilities across multiple (sub)disciplines in the field, including match and performance analysis, exercise physiology, training science, or collective movement behavior analysis. As an example, player tracking data has been used extensively to analyze physical