Edgewater Crime Rate Trends — Chicago
Edgewater is a North Side lakefront neighborhood between Foster Avenue and Devon Avenue, organized around the CTA Red Line's Bryn Mawr, Granville, and Thorndale stations. Mixed lakefront high-rises and brick two-flats, anchored by the Andersonville commercial strip on Clark Street and the Bryn Mawr Historic District.
Two categories moved in Edgewater this August, both structural. Burglary and vandalism each registered as sustained shifts downward, meaning the change isn't a single quiet month but a multi-month pattern embedded in the trailing 12-month window. The overall shape is narrow and directionally consistent: two signals, both decreases, no spikes or rare events.
Burglary is the stronger of the two, down 46.8% against the prior 12 months, 83 incidents in the current period against 156 in the year before. Vandalism follows a similar arc, off 37.2% year-over-year, 187 incidents vs. 298. Everything else in the tracked categories, robbery, aggravated assault, motor vehicle theft, and other larceny, ran within range this month, though several also show year-over-year declines in the 12-month totals.
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.
- Vandalism has reset to a lower baseline.
The trailing 12-month count is 187, down 37% from 298 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
- Burglary has reset to a lower baseline.
The trailing 12-month count is 83, down 47% from 156 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 August 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 Edgewater compares
Peer neighborhoods picked by closest 12-month burglary 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 burglary levels.”
Recurring local terms (last 12 months)
Top terms in incident descriptions for Edgewater, 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.