Mount Greenwood Crime Rate Trends — Chicago
Mount Greenwood is a Far South Side neighborhood on the Worth and Evergreen Park borders, organized around 111th Street and Pulaski Road. Predominantly single-family ranch homes, with Mount Greenwood Park and the Daniel Wright Woods forest preserve as community anchors.
June 2026 was a quiet month for Mount Greenwood. No tracked category crossed an anomaly threshold — zero signals across the full crime mix — making this one of the calmer briefings in the recent record.
The 12-month picture is more mixed. Violent crime is broadly lower: robbery is down 40.0% year-over-year (3 incidents vs. 5), sexual assault down 42.9% (4 vs. 7), and aggravated assault down 25.0% (9 vs. 12). Property crime tilts the other way — burglary is up 40.0% over the same window (14 vs. 10) and motor vehicle theft up 18.2% (26 vs. 22), though neither generated a signal this month. Everything else in June fell within normal range.
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.
No sustained shifts surfaced this month.
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
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.
Vandalism
How Mount Greenwood 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.”
Riverdale
114 incidents over the past 12 months — 6 above Mount Greenwood's 108.
Open page →Fuller Park
100 incidents over the past 12 months — 8 below Mount Greenwood's 108.
Open page →Forest Glen
99 incidents over the past 12 months — 9 below Mount Greenwood's 108.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Mount Greenwood, 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.