"Does 4-4-2 exist?": An Analytics Approach to Understand and Classify Football Team Formations in Single Match Situations

Research output: Chapter in Book/Report/Conference proceedingConference contribution - Article for conferenceResearch


  • Eric Müller-Budack
  • Jonas Theiner
  • Robert Rein
  • Ralph Ewerth

Research units


The chance to win a football match can be significantly increased if the right tactic is chosen and the behavior of the opposite team is well anticipated. For this reason, every professional football club employs a team of game analysts. However, at present game performance analysis is done manually and therefore highly time-consuming. Consequently, automated tools to support the analysis process are required. In this context, one of the main tasks is to summarize team formations by patterns such as 4-4-2 that can give insights into tactical instructions and patterns. In this paper, we introduce an analytics approach that automatically classifies and visualizes the team formation based on the players’ position data. We focus on single match situations instead of complete halftimes or matches to provide a more detailed analysis. The novel classification approach calculates the similarity based on pre-defined templates for different tactical formations. A detailed analysis of individual match situations depending on ball possession and match segment length is provided. For this purpose, a visual summary is utilized that summarizes the team formation in a match segment. An expert annotation study is conducted that demonstrates 1) the complexity of the task and 2) the usefulness of the visualization of single situations to understand team formations. The suggested classification approach outperforms existing methods for formation classification. In particular, our approach gives insights into the shortcomings of using patterns like 4-4-2 to describe team formations.
Original languageEnglish
Title of host publicationMMSports 2019 - Proceedings of the 2nd International Workshop on Multimedia Content Analysis in Sports, co-located with MM 2019 : proceedings of the 2nd International Workshop on Multimedia Content Analysis in Sport, October 25, 2019, Nice, France
EditorsRainer W. Lienhart, Thomas B. Moeslund, Hideo Saito
Number of pages9
Place of PublicationNew York
PublisherThe Association for Computing Machinery
Publication date15.10.2019
ISBN (Print)9781450369114
ISBN (Electronic)978-1-4503-6911-4
Publication statusPublished - 15.10.2019
EventInternational Workshop on Multimedia Content Analysis in Sports - Nice, France
Duration: 25.10.201925.10.2019
Conference number: 2

ID: 5213995


View graph of relations