Automatic Extraction of the Passing Strategies of Soccer Teams

TL;DR

This paper introduces a method using Dynamic Time Warping to analyze soccer ball trajectories and infer team tactics, providing insights into passing strategies and styles from season-long data.

Contribution

It presents a novel approach to reverse-engineering soccer tactics from trajectory data, focusing on pattern analysis of repeated event sequences.

Findings

Identified passing strategies for possession and counter-attacks

Revealed team and individual passing styles

Analyzed season-long trajectory data for tactical insights

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.