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Football passing decisions predicted by new Graph Neural Network

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a Graph Neural Network (GNN) framework to predict receiver selection in professional football. This Message-Passing Neural Network (MPNN) models on-field interactions as dynamic graphs, representing players as nodes and passing lines as edges with various metrics. Trained on tracking and event data, the model demonstrates competitive accuracy in identifying actual receivers and achieves state-of-the-art results for top-three suggestions, offering performance analysts a tool to evaluate numerous passes quickly. AI

IMPACT This research introduces a novel application of GNNs for sports analytics, potentially enhancing performance evaluation and strategy development.

RANK_REASON The cluster contains an academic paper detailing a new machine learning approach for a specific domain.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Football passing decisions predicted by new Graph Neural Network

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The cluster contains an academic paper detailing a new machine learning approach for a specific domain.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Gabriel Masella, Giuseppe Alessio D'Inverno, Max Goldsmith, Gianluigi Rozza ·

    Evaluating passing decision-making in professional football: An enhanced MPNN approach to Receiver Selection

    arXiv:2605.25696v1 Announce Type: new Abstract: The process of decision-making in football is characterized by a complex interplay between spatial positioning, opponent pressure, and player intent. This work introduces a Graph Neural Network (GNN) framework designed to predict Re…

  2. arXiv cs.LG TIER_1 English(EN) · Gianluigi Rozza ·

    Evaluating passing decision-making in professional football: An enhanced MPNN approach to Receiver Selection

    The process of decision-making in football is characterized by a complex interplay between spatial positioning, opponent pressure, and player intent. This work introduces a Graph Neural Network (GNN) framework designed to predict Receiver Selection, the optimal passing target, by…

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