How the score works
Outflock scores an address by the routes out of it, not by the cameras near it. This page covers what the score measures, what the grades mean, where the camera data comes from, and what the score leaves out.
What the score measures
The score asks one question: if you leave this address on an ordinary short trip, like a run to the store, school, or a friend's place, how likely is it that a license plate reader (ALPR) logs your car on the way?
Being near cameras is not the same as being exposed to them. Ten cameras along one highway you rarely drive matter less than three cameras on the only roads out of your neighborhood. So Outflock looks at the ways out, not the camera count.
A score of 100 means none of the simulated trips out passed a mapped reader. A score of 0 means every one did.
What the grades mean
Each result shows a letter grade and the count behind it, like “2 of 8 exits logged”. The grade follows from the share of trips that were logged. The bands were checked against reference addresses ranging from rural areas with no mapped cameras to dense city grids with hundreds.
| Grade | Score | What it means |
|---|---|---|
| A | 85 – 100 | Low exposure. Few or no trips out are logged. |
| B | 70 – 84 | Light exposure. Some trips out are logged, and there are clear ways out that are not. |
| C | 50 – 69 | Moderate exposure. About a third to half of trips out are logged. |
| D | 30 – 49 | High exposure. More than half of trips out are logged. |
| F | 0 – 29 | Very high exposure. Most or all trips out are logged. |
How a score is worked out
Where the camera locations come from
Camera locations come from OpenStreetMap, the open map anyone can edit. Volunteers, including the DeFlock community, add license plate readers as they spot them. Because the data is open, anyone can check it or add a missing camera. It is most complete where many people contribute, usually cities, and thinner where few do.
How the trips are modeled
From the address, Outflock plans short, errand-length trips on real roads, one in each of several directions. A trip counts as logged if it passes close to a mapped reader. The score is the percentage of trips that were not logged. The radius you choose on the score page sets which cameras count: a larger radius includes cameras farther from the address.
How the data stays current
Outflock takes a fresh census of every mapped reader in the US on a regular schedule. New cameras appear after they are mapped, and cameras removed from the map drop out. Each result shows the date of the census it used. Counts from past censuses are kept, so the score page can show whether coverage in the surrounding area is growing, shrinking, or holding steady.
What the score leaves out
The score is only as complete as the open data behind it, and it covers one kind of surveillance. Keep these limits in mind when reading a result.
- •Unmapped cameras do not count. If nobody has added a reader to the map, the score cannot see it. Coverage is thinner in rural areas and in places with few contributors.
- •Only license plate readers are included. Other cameras, such as CCTV, doorbell cameras, and readers mounted on police cars, are not part of the score.
- •A camera's facing direction is not used. A trip counts as logged if it passes close to a reader, whichever way the camera points.
- •Every reader counts the same. The score does not yet account for who operates a camera or how widely its data is shared.
- •Your routine may differ. The score models short trips in several directions. If most of your driving goes one way, your real exposure can be higher or lower than the grade.
- •Recent changes take time to show. A new camera appears only after someone maps it and the next census runs.