Automatic Extraction of the Passing Strategies of Soccer Teams
August 10, 2015 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Laszlo Gyarmati, Xavier Anguera
arXiv ID
1508.02171
Category
cs.CV: Computer Vision
Cross-listed
stat.ML
Citations
36
Venue
arXiv.org
Last Checked
6 months ago
Abstract
Technology offers new ways to measure the locations of the players and of the ball in sports. This translates to the trajectories the ball takes on the field as a result of the tactics the team applies. The challenge professionals in soccer are facing is to take the reverse path: given the trajectories of the ball is it possible to infer the underlying strategy/tactic of a team? We propose a method based on Dynamic Time Warping to reveal the tactics of a team through the analysis of repeating series of events. Based on the analysis of an entire season, we derive insights such as passing strategies for maintaining ball possession or counter attacks, and passing styles with a focus on the team or on the capabilities of the individual players.
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