North Cleveland Park Crime Rate Trends — Washington DC
North Cleveland Park is a mid-Northwest residential pocket along the Connecticut Avenue corridor, with its commercial life concentrated at the Van Ness Metro station to the south and Forest Hills' single-family streets to the east. The cluster shares the Connecticut Avenue spine with Forest Hills and Van Ness, three quiet residential neighborhoods that share a Metro and a school district but not a tight commercial center.
North Cleveland Park registered a single signal in June 2026 — one sustained shift in Other Larceny, with no spikes, drops, or rare events elsewhere. Every other tracked category ended the month within normal range.
The Other Larceny shift is structural, not a one-month dip: the trailing 12-month total is 118 incidents against 206 in the prior 12 months, a 42.7% reduction that reflects a multi-year repositioning rather than a quiet patch. Theft from Vehicle is also down 19.4% year-over-year (54 vs. 67), and Robbery is down 20.0%, though neither crossed the threshold for a formal signal this month. The breadth of declines across property categories is consistent, even if only one met the sustained-shift standard.
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.
- Other Larceny has reset to a lower baseline.
The trailing 12-month count is 118, down 43% from 206 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
What next month likely looks like
Forecasts trained through June 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
Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.
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 North Cleveland Park compares
Peer neighborhoods picked by closest 12-month other larceny 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 other larceny levels.”
Fairfax Village
122 incidents over the past 12 months — 4 above North Cleveland Park's 118.
Open page →Capitol View
124 incidents over the past 12 months — 6 above North Cleveland Park's 118.
Open page →Douglas
135 incidents over the past 12 months — 17 above North Cleveland Park's 118.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for North Cleveland Park, 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.