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AI player recognition

It reads the number first. References fill the gaps.

Jersey numbers matched against your event roster remain the primary signal. When a number is hidden, an organisation can deliberately enable reference comparison for its players. A clear face may be one cue alongside hair, build and stable appearance; kit colour, pose and a single look alone are never enough to publish a match.

Primary signals

  • Person detection
  • Jersey-number OCR
  • Your roster
  • Team and burst context

Reference safeguards

  • Off until your organisation enables it
  • Limited to your organisation and roster
  • Single appearance signals never auto-publish
  • Multi-signal matches require two reference views
  • Player opt-out deletes their reference data
7
#794%
7Marek KowalskiHigh confidence
11Ida PetersenReview recommended

How a photo is processed

  1. 01

    Detect people

    Every frame is scanned for players. A crowd shot with nobody in focus resolves to nothing and costs you no review time.

  2. 02

    Find the jersey region

    The area of the shirt likely to carry a number is isolated — front, back or angled.

  3. 03

    Read the number

    OCR tuned for the shapes that actually go wrong: 1 and 7, 5 and 6, 8 and 0, and a leading digit hidden by an arm.

  4. 04

    Match the roster

    The number is searched only within the teams attached to the event. Seven is ambiguous across a league and near-unique inside one match.

  5. 05

    Combine independent signals

    When a number is hidden, clear facial identity, matching kit, several reference views, the event roster and person-level burst tracking can corroborate one another.

  6. 06

    Assign or ask

    Only an unambiguous multi-signal result is assigned automatically. A single face, similar kit, pose or loose resemblance stays in review.

Your corrections matter, but they do not retrain anything

Every correction is captured as structured feedback: what was predicted, what you chose, the model version, and the frame it came from. None of it retrains a model automatically. It remains inside the organisation as reviewable correction data. A player can be excluded from AI assignment, which also deletes uploaded references and derived appearance data for that player.

See it on your own match

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