# Structural Pass Analysis in Football: Learning Pass Archetypes and Tactical Impact from Spatio-Temporal Tracking Data

arXiv: https://arxiv.org/abs/2603.28916 · HTML: https://mlsanity.com/paper/2603.28916/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 24 references that are in the map.
- First posted on arXiv 30 Mar 2026.

## Builds on (most cited first, 7 of 7)

- [Actions Speak Louder Than Goals: Valuing Player Actions in Soccer](https://mlsanity.com/paper/1802.07127/) (2018)
- [A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions](https://mlsanity.com/paper/2011.09426/) (2020)
- [A Machine Learning Approach for Player and Position Adjusted Expected Goals in Football (Soccer)](https://mlsanity.com/paper/2301.13052/) (2023)
- [Classification of Passes in Football Matches using Spatiotemporal Data](https://mlsanity.com/paper/1407.5093/) (2014)
- [Bayes-xG: Player and Position Correction on Expected Goals (xG) using Bayesian Hierarchical Approach](https://mlsanity.com/paper/2311.13707/) (2023)
- [Through the Gaps: Uncovering Tactical Line-Breaking Passes with Clustering](https://mlsanity.com/paper/2506.06666/) (2025)
- [What If They Took the Shot? A Hierarchical Bayesian Framework for Counterfactual Expected Goals](https://mlsanity.com/paper/2511.23072/) (2025)

## Abstract (arXiv)

Passing actions are commonly evaluated through ball progression and attacking outcomes, yet their relationship with the spatial organisation of the opposition provides an additional perspective on passing behaviour. This study introduces an interpretable framework for describing passing structure using synchronised event and tracking data. Three complementary descriptors are proposed: Line Bypass Score (LBS), measuring the difference in goal-side opponent counts between passer and receiver; Space Gain Metric (SGM), comparing their nearest-opponent distances; and Structural Disruption Index (SDI), summarising differences in defensive organisation between pass initiation and a sampled state one second later. Following transformation and standardisation, these descriptors are combined into Tactical Impact Value (TIV), a fixed-weight structural composite. Applied to 41,078 open-play passing events from the 2022 FIFA World Cup, the framework identifies four interpretable profiles: Circulatory, Destabilising, Line-breaking, and Space-expanding. The profiles exhibit distinct structural signatures and different distributions of territorial-crossing and recorded attacking indicators. Team, spatial, player, and passer--receiver analyses further demonstrate how the representation can describe passing behaviour across analytical scales. The framework complements outcome-oriented approaches by connecting individual passing actions with measurable characteristics of opposition positioning and defensive organisation.