A single injury-risk score compresses very different situations into the same number. It also hides uncertainty and missing data. We no longer build the staff workflow around a score or an injury probability.
Clinical judgement needs a discussion. A head physiotherapist must be able to return to the source, inspect the trajectory and explain why this player is different today.
Omen therefore brings together observable indicators: training load, form, freshness, test results, reported pain, relevant history and missing measurements.
Each indicator keeps its source, time window and recent evolution. The interface highlights what changed without ranking players by a supposed probability of injury.
The AI can formulate a concise, qualitative reading of the observed factors. It does not produce a diagnosis or probability; it states what supports the reading and what information is missing.
The staff can then add context: a planned load, travel, an adapted session, a reassuring examination or a conversation with the player. That context remains visible for the next review.
A decision may follow — adapt the load, schedule recovery, run a test or simply keep monitoring. The tool prepares the information; the staff interprets it and decides.
We apply the same principle to prevention and return to play. Omen prepares a progression from the player's history and current indicators, while every validation and change remains with the staff and in the audit trail.