Generalized Action-based Ball Recovery Model using 360$^\circ$ data

TL;DR

This paper introduces a generalized model for analyzing ball recovery actions in soccer using 360-degree data, aiming to understand the influence of positioning and actions on possession changes.

Contribution

It presents a novel, comprehensive model for evaluating ball recovery actions based on 360-degree data, expanding beyond traditional methods.

Findings

Identifies key actions leading to ball recovery

Analyzes the impact of team positioning on recovery success

Evaluates defensive dynamics under different pressing styles

Abstract

Even though having more possession does not necessarily lead to winning, teams like Manchester City, Liverpool, and Leeds United notably have tried to recover the ball quickly after they lost it over the past few years. Nowadays, some of the top managers in the world apply high-pressing styles, and concepts such as the five-second rule, usually credited to Guardiola, have been spreading out [9][10], becoming a fundamental part of how lots of teams have played over the recent years. Expressions like "don't let them breathe" and "get the ball back as soon as possible" are often heard in the media [4][5][6], but what are the actions that most lead to a change in possession? What is the influence of a team's positioning on the ball recovery? Which are the players that more often collapse when under pressure? Can we evaluate the defensive dynamics of teams that do not necessarily press the player in possession as intensely as those mentioned above? We try to answer those and other questions in this paper by creating a Generalized Action based Ball Recovery model (GABR) using Statsbomb 360$^\circ$ data.