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.
September 2026 was a genuinely quiet month for Mount Greenwood. No tracked category crossed the anomaly threshold, and the signal count for the period is zero across all types, spikes, drops, sustained shifts, and rare events alike.
The 12-month trend lines tell a mixed but mostly stable story. Motor vehicle theft is the sharpest mover in the trailing year, 25 incidents against 19 in the prior period, a 31.6% rise, while vandalism moved the opposite direction, 39 incidents against 56, down 30.4%. Robbery sits at 3 incidents over the current 12 months compared to 6 in the year before, and other larceny edged up 10.5% to 105 incidents. Nothing in September itself broke from those gradual trajectories.
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 September 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
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.
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.”
Forest Glen
91 incidents over the past 12 months — 14 below Mount Greenwood's 105.
Open page →Fuller Park
120 incidents over the past 12 months — 15 above Mount Greenwood's 105.
Open page →Riverdale
134 incidents over the past 12 months — 29 above Mount Greenwood's 105.
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.