Pressing Intensity: An Intuitive Measure for Pressing in Soccer

2024-12-30

arXiv.org

AI Summary

Existing football pressing intensity metrics often neglect player velocity, movement direction, and reaction time, limiting their ability to accurately and dynamically characterize pressing situations. This paper proposes a frame-level pressing intensity quantification framework grounded in optical tracking data. It introduces, for the first time, a velocity- and direction-aware time-to-intercept (TTI) model integrated with a Spearman-inspired spatial control principle; through a logistic transformation, TTI is converted into an interpretable, player-specific pressing probability. The method enables per-frame visualization and quantitative assessment of pressing intensity, substantially improving detection accuracy. It facilitates tactical pattern discovery, fine-grained situational analysis, and the derivation of novel performance indicators. By providing a robust, interpretable computational foundation, this framework advances high-fidelity tactical analysis in elite football.

Technology Category

• Computer Vision: Motion & Tracking
• Search and Optimization: Evaluation and Analysis
• Intelligent Robots: State Estimation

Application Category

• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Security and Privacy: Large-scale security measurements

Abstract

Pressing is a fundamental defensive strategy in football, characterized by applying pressure on the ball owning team to regain possession. Despite its significance, existing metrics for measuring pressing often lack precision or comprehensive consideration of positional data, player movement and speed. This research introduces an innovative framework for quantifying pressing intensity, leveraging advancements in positional tracking data and components from Spearman's Pitch Control model. Our method integrates player velocities, movement directions, and reaction times to compute the time required for a defender to intercept an attacker or the ball. This time-to-intercept measure is then transformed into probabilistic values using a logistic function, enabling dynamic and intuitive analysis of pressing situations at the individual frame level. the model captures how every player's movement influences pressure on the field, offering actionable insights for coaches, analysts, and decision-makers. By providing a robust and intepretable metric, our approach facilitates the identification of pressing strategies, advanced situational analyses, and the derivation of metrics, advancing the analytical capabilities for modern football.

Problem

• Lack of precise metrics for measuring pressing in soccer
• Insufficient use of positional data and player movement
• Need for dynamic analysis of pressing intensity

Innovation

• Integrates player velocities and movement directions
• Uses logistic function for probabilistic time-to-intercept
• Leverages Spearman's Pitch Control model components