| Literature DB >> 28113148 |
Manuel Stein, Halldor Janetzko, Thorsten Breitkreutz, Daniel Seebacher, Tobias Schreck, Michael Grossniklaus, Iain D Couzin, Daniel A Keim.
Abstract
For development and alignment of tactics and strategies, professional soccer analysts spend up to three working days manually analyzing and annotating professional soccer matches. In an effort to improve soccer player and match analysis, a visual-interactive and data-analysis support system focuses on key situations by using rule-based filtering and automatically annotating key types of soccer match elements. The authors evaluate the proposed approach by analyzing real-world soccer matches and several expert studies. Quantitative measures show the proposed methods can significantly outperform naive solutions.Year: 2016 PMID: 28113148 DOI: 10.1109/MCG.2016.102
Source DB: PubMed Journal: IEEE Comput Graph Appl ISSN: 0272-1716 Impact factor: 2.088