Englewood Crime Rate Trends — Chicago
Englewood is a South Side neighborhood organized around 63rd and Halsted Streets, historically one of the city's largest commercial centers. Bordered by the Dan Ryan Expressway and Garfield Boulevard; anchored by Hamilton Park, Kennedy-King College, and the Ogden Park field house.
Three signals surfaced in Englewood this June — two one-month below-trend readings and one sustained structural shift. The shape of the month is consistent: robbery is running lower both as a single-month signal and as a multi-year structural pattern, with vandalism adding a second below-trend reading across property crime.
Robbery is the clearest mover. The trailing 12-month total stands at 134 incidents, down 35.0% against the prior year's 206 — and well below the multi-year baseline of 211.33. Vandalism also ran below trend this month, with a 12-month total of 509 against 616 the year before, a 17.4% decline. Every other tracked category — aggravated assault, burglary, motor vehicle theft, other larceny — moved less than the flagged categories and did not cross the signal threshold.
Notable signals 2
Robbery
The past 12 months saw 134 incidents — about 37% below the 211 average from prior years.
Vandalism
The past 12 months saw 509 incidents — about 20% below the 635 average from prior years.
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.
- Robbery has reset to a lower baseline.
The trailing 12-month count is 134, down 35% 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.
Arson
Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.
Burglary
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.
Vandalism
How Englewood compares
Peer neighborhoods picked by closest 12-month robbery 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 robbery levels.”
Recurring local terms (last 12 months)
Top terms in incident descriptions for Englewood, 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 CPD's open dataset on the City of Chicago Open Data portal — IUCR-coded and mapped to 9 UCR-aligned categories (theft from vehicle isn't reliably separable in the public feed and rolls into other larceny). Aggregated to community area × category × month.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.