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Sport · Applied data science · R&D

Active R&D

The same action can mean something different in a different game situation.

The challenge

Counts of passes, shots, assists or turnovers only tell part of the story. Meaning also depends on what preceded an action, where it occurred, who was involved and the configuration of play around it.

What we’re exploring

Panalogy Sports investigates morphological and systems-oriented approaches that represent actions as configurations. Initial applications span elite sporting data, contextual sequences and creative actions in football, with emerging morphological work in basketball.

What the approach can combine

  • Event and tracking data with spatial and game-state context.
  • Actions before and after an event.
  • Player and team configurations.
  • Morphological representations and interaction networks.
  • Statistical models and applied machine learning.

Where it could lead

Richer representations of the game may support questions about tactics, player evaluation, creativity, recruitment and decision support. These are active research directions rather than claims of proven competitive gains.

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