On-track Incident
Confirmed likely stopped car or on-track incident is active. Use binary_sensor.f1_on_track_incident in dashboards, templates, and automations.
See live data availability for session and data-source requirements. The details below describe any additional conditions for this entity.
These are standard entity IDs. If Home Assistant assigned a different ID, or you renamed an entity, use your existing ID in the examples.
State and attributes
binary_sensor.f1_on_track_incident - On while F1 Sensor has a confirmed likely stopped car or on-track incident for the active session.
This entity detects likely stopped cars and on-track incidents from live timing, track status, and Race Control context. It does not prove that a crash happened, and it may also represent a technical failure, spin, red flag stop, or another neutral on-track situation.
State (on/off)
onwhen at least one confirmed incident is active.offwhen no confirmed incident is active.unavailablewhen live or replay data is not available enough to report a reliable state.
Example
on
Attributes
| Attribute | Type | Description |
|---|---|---|
| active_count | number | Number of confirmed active incidents |
| highest_confidence | string | Highest active confidence: medium or high |
| latest_incident_id | string | Stable identifier for the most recent incident update |
| latest_driver_number | string | Car number for the latest incident update |
| latest_driver_tla | string | Driver abbreviation for the latest incident update |
| latest_reason | string | Neutral reason code for the latest update |
| latest_phase | string | Latest phase: candidate, confirmed, updated, or cleared |
| session_type | string | Lowercase session type, such as race, sprint, qualifying, or practice |
| session_name | string | Human-readable session name |
| data_quality | string | Data source quality, such as live, replay, stale, or bootstrap |
The entity intentionally keeps attributes small and stable. Use the f1_sensor_incident event for detailed automation triggers and notification text.
For the full behavior, confidence, and notification model, see Incident Detection.
Incident detection is designed for race, sprint, qualifying, and practice sessions. Practice alerts are more conservative because practice sessions naturally contain more slow running, pit activity, and testing-style behavior.