Georgetown Crime Rate Trends — Washington DC
Georgetown is the West Side waterfront neighborhood of Federal-era rowhouses, the Georgetown University campus, and the C&O Canal towpath, with its commercial spine running along M Street and Wisconsin Avenue. The cluster also covers Burleith and Hillandale to the north, two compact pre-war residential pockets that sit between the campus and Glover Park.
April 2026 produced a single signal in Georgetown — one sustained shift, no spikes, no drops, no rare events. The month's story is narrow: theft from vehicle is structurally higher over the trailing 12 months, not just a noisy one-month read.
Theft from vehicle is up 81.8% against the prior 12-month period — 180 incidents vs. 99 — and the sustained-shift classification reflects that this gap has held across multiple months, not a single outlier. Every other tracked category stayed within range: burglary is actually down 78.9% year-over-year (4 incidents vs. 19), robbery edged up 14.3% on thin volume (8 vs. 7), and motor vehicle theft and other larceny moved less than 10% in either direction.
Notable signals 0
Nothing notable surfaced this month — every category sits within normal range against its baseline.
All categories, last 24 months
Each panel: recent monthly count vs. trailing 12-month context. MoM is the most recent month vs. the one before; 12mo YoY compares the trailing year to the year before that.
What's been quietly true for a year
Spikes get attention. Sustained shifts shape policy. These are multi-quarter patterns where the past 12-month total differs meaningfully from the year before — they often precede the baseline resetting.
- Theft from Vehicle is climbing.
The trailing 12-month count is 180, up 82% from 99 the year before. If the trend holds another quarter, it will pull the multi-year baseline up.
What next month likely looks like
Forecasts trained through April 2026, with a likely range we're 95% confident the actual count will fall inside. Categories with too little recent volume — or violent categories at the neighborhood level — show no forecast and are surfaced through signals above instead. See the methodology page for the gating rules.
Aggravated Assault
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Burglary
Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.
Homicide
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Motor Vehicle Theft
Other Larceny
Robbery
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Sexual Assault
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Theft from Vehicle
How Georgetown compares
Peer neighborhoods picked by closest 12-month theft from vehicle volume — a pragmatic v1 of peer matching. Demographic / housing-stock peer matching isn't built yet (we deliberately don't ingest income or race data alongside crime). Volume similarity has the right intuition: “neighborhoods experiencing comparable theft from vehicle levels.”
Ivy City
180 incidents over the past 12 months — 0 below Georgetown's 180.
Open page →Downtown
173 incidents over the past 12 months — 7 below Georgetown's 180.
Open page →Brookland
169 incidents over the past 12 months — 11 below Georgetown's 180.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Georgetown, excluding generic crime taxonomy. Useful as texture — what kinds of specifics show up here that don't show up elsewhere.
Hour-of-day, day-of-week, and seasonality
Distribution of bucketed incidents in this neighborhood across the full analysis window. Useful for routine context — shopping-strip thefts vs. late-night assaults read very differently when you can see when each typically happens.
How we built this page
Data → Anomalies → Forecast → Page
Incident data is pulled from DC Open Data — MPD's per-year Crime Incidents layers on the DCGIS ArcGIS Hub — mapped to 8 UCR Part 1 categories (vandalism and arson are not exposed in MPD's public feed and are excluded). The feed covers 2018-current and updates daily. Aggregated to neighborhood cluster × category × month, with each cluster page identified by its colloquial lead constituent (Adams Morgan, Petworth, Capitol Hill, etc.) rather than the numbered 'Cluster N' identifier.Anomalies are surfaced using strict thresholds (~p < 0.01). Forecasts are Prophet with low-count gating; violent categories at the neighborhood level skip the forecast and show rare-event / streak signals instead.
Spike rule: 12-mo total > baseline mean + 2.5σ AND ≥ 20 incidents AND 6-mo confirms. Drop rule: 12-mo total < baseline mean − 2.5σ AND baseline mean ≥ 20. Rare event: any incident in the last 90 days, no prior comparable in ≥ 5 years.