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Pressing Intensity Stats: How High-Press Football Affects AI Predictions

2026-03-28 Statistiques
Pressing
PPDA
High Press
Defensive Intensity
Statistics

Pressing intensity has become one of the defining tactical characteristics of modern football, and its statistical measurement provides valuable input for AI prediction models. At 1X2.TV, we incorporate detailed pressing metrics into our match analysis framework.

PPDA: Passes Per Defensive Action

PPDA (Passes Per Defensive Action) is the primary metric for measuring pressing intensity. It counts how many passes the opposition completes before the pressing team makes a defensive action. Lower PPDA indicates more intense pressing. Top pressing teams like Liverpool under Klopp or Leverkusen under Alonso achieve PPDA values below 8, while passive defensive teams allow 12 or more passes per defensive action. Our models use PPDA to classify team styles and predict match dynamics.

High Turnovers and Pressing Effectiveness

The ultimate goal of pressing is to win the ball in dangerous areas. We track high turnovers (ball recoveries in the final third) and the expected goals generated from sequences beginning with high turnovers. Teams that combine intense pressing with effective exploitation of high turnovers present a distinct threat that our models quantify.

Pressing Sustainability

Sustaining high pressing intensity across 90 minutes is physically demanding. Our models track pressing intensity variation across match halves and identify teams whose pressing fades significantly in the second half. This temporal pressing profile informs our predictions about when goals are likely to occur in matches involving pressing teams.

Press Resistance

Some teams are exceptionally effective at playing through high pressing, maintaining possession quality even under intense pressure. Our models calculate a press resistance score that quantifies how well teams retain the ball and generate chances despite opponent pressing. When a strong pressing team faces a press-resistant opponent, the interaction effect is factored into predictions.


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