SOURCE-LINKED INTELLIGENCE
SambaGraph: Action-Reaction Spatio-Temporal Graphs for Soccer Tactical Response Modeling
Soccer tactics are interactive: an attacking action changes the opponent's defensive problem, and the observed response depends on the multi-agent match state. We introduce SambaGraph, an action--reaction spatio-temporal graph dataset and benchmark for soccer tactical response modeling. From tracking and event data for all 64 matches of the 2022 FIFA World Cup, we curate 4,070 action-centered episodes represented as temporally aligned 23-node player--ball graph sequences with attack/defense views, response labels, and 26,270 split-safe attack--defense pairs. We study three questions: whether o
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-22T02:02:02.000Z
First collected: 2026-09-23T04:21:13.910Z. This is not the publication date.