The use of player tracking data to analyze defensive play in professional soccer-A scoping review

The analysis of tracking data in tactical game analysis is a topic of rising interest, as more detailed insights into performance structure in soccer can be obtained compared to traditional (e.g. notational) analyzes. Compared to the variety and detailed analyzes of offensive play, the number of studies analyzing the defensive play is low. However, in recent years, an increasing number of studies investigating defensive play have been published, so it seems useful to provide an overview of the current state of research in this area. Therefore, this study aims to identify the approaches that have been used to analyze the defensive play in professional soccer using player tracking data and to reveal the findings on successful defensive play. A systematic literature search of electronic databases (PubMed (n = 604), Web of Science (n = 593), and SPORTDiscuss (n = 872)) was conducted according to the PRISMA extension for Scoping Reviews (PRISMA-ScR). Studies that were included used tracking data of professional adult male soccer and analyzed defensive play. The result is a total of 23 studies that were analyzed in detail using the standardized quality assessment checklist for systematic reviews in sports science. The synthesis of results was carried out descriptively by organizing the results into different levels of tactical play (individual level, group level, team level). All included studies were of good methodological quality. The approaches to investigate defensive play using tracking data are highly heterogeneous (e.g. analysis of defensive pressure, analysis of synchronization, behavioral analyzes, ball recoveries). Successful defensive play is characterized by high pressure at the individual level, by high inter-team and intra-team synchronization and balanced defense at the group level, and by a compact coordinated organization at the team level. By summarizing the state of research on defensive play in soccer using sophisticated analysis approaches that showcase the possibilities of tracking data, this study provides an important foundation for future research in this area.