Methodology

How we build safety scores from public data

What CrimeLayer Measures

CrimeLayer produces a single safety score (0–100) and letter grade (A through F) for every city in its dataset, computed from the most recent year of FBI Uniform Crime Report (UCR) data available for that city.

The score answers a specific question: "Relative to other cities in the same state, how does this city's aggregate crime rate compare?"

It does not answer:

Data Source

The underlying data is the FBI's Uniform Crime Report (UCR), a federal annual crime dataset published each September covering the previous calendar year. UCR data is public domain.

For efficiency, CrimeLayer currently sources UCR data via the DW Data community CSV redistribution, which aggregates FBI UCR files into a consistent schema. This is the same underlying FBI data, just in an easier-to-parse format.

More detail on sources, data years, and coverage is available on the Sources and Coverage pages.

How the Score Is Calculated

Step 1: Crime Weighting

Each reported crime type is multiplied by a severity weight that reflects its impact on family and community safety perception:

Crime TypeWeight
Murder / non-negligent manslaughter10
Rape9
Aggravated assault8
Robbery7
Arson5
Burglary4
Motor vehicle theft3
Larceny / theft2

Step 2: Weighted Rate per 1,000 Population

For each city, we sum the weighted crime counts and divide by population (in thousands) to get a comparable per-capita rate.

Step 3: Percentile Ranking Within State

Every city is then ranked against every other reported city in the same state by its weighted rate, ascending (safest first). The safety score is that city's percentile position in its state:

⚠️ Important: Why Large Cities Often Get F Grades

Per-state percentile ranking produces counterintuitive results for large metropolitan cities. Consider Chicago, Illinois:

  • Illinois has ~470 cities reporting to FBI UCR
  • The vast majority are small suburbs and rural towns with near-zero absolute crime counts
  • Chicago's weighted crime rate per 1,000 residents is moderate in absolute terms, but higher than 95%+ of other Illinois cities
  • Result: Chicago receives a safety score in the single digits and a grade of F

The same pattern affects Houston, New York City, Los Angeles, Philadelphia, and every other major US metropolitan area. This does not mean these cities are "unsafe" in an absolute sense. It means they have more aggregate crime activity than the small suburbs they're being compared against in their state ranking.

If you are displaying CrimeLayer scores to end users, please include context that clarifies the score is a relative ranking, not an absolute safety measurement. For major metropolitan cities, consider showing both the score and a qualifier like "ranked in the lower percentile of Illinois cities by aggregate crime rate" rather than simply "F — High Crime."

A future version of CrimeLayer may introduce a city-size-adjusted grading method that compares large cities against other large cities. Until then, the per-state ranking method is what the API returns.

What the Score Should NOT Be Used For

Per our Acceptable Use Policy, CrimeLayer data must not be used for:

The data is aggregate, area-wide context. Treating it as individual-level information would be both methodologically wrong and legally risky.

Data Freshness

FBI UCR data is released annually in September for the previous calendar year. CrimeLayer refreshes its dataset when new UCR data becomes available. Every API response includes a _meta.data_year and _meta.last_updated field so consumers can see exactly how fresh the underlying data is.

See the Changelog for refresh history.

Missing Cities and States

Some cities do not report to FBI UCR (participation is voluntary). In those cases, the API returns a 404 with a state_average fallback. See the Coverage page for a state-by-state breakdown of what's included.

Florida is currently missing. Florida does not participate fully in the FBI NIBRS program, so its cities do not appear in the DW Data redistribution. A Florida-specific source (FDLE) will be added in a future release.

Questions, Corrections, Feedback

If you notice a data error, methodology question, or want to contribute a better grading approach, email data@crimelayer.com or open an issue on GitHub.