Hegewisch Crime Rate Trends — Chicago
Hegewisch is a Far Southeast Side neighborhood on the Indiana border, founded in 1883 as a planned company town for the U.S. Rolling Stock Company. Bordered by the Wolf Lake forest preserve and the Calumet River industrial corridor; predominantly single-family homes with a small commercial strip on Baltimore Avenue.
Three signals moved in Hegewisch this March — one fresh spike and two sustained structural shifts. The shape is uneven: vandalism is running sharply above trend on multiple timescales, while other larceny has quietly moved in the opposite direction over the past year.
Vandalism is the dominant story. The current 12-month total is 158 incidents against a prior-year count of 92 — a 71.7% rise year-over-year — and the month also registered a one-month spike on top of that structural shift. Other larceny, by contrast, is down 26.6% over the same window, falling from 184 to 135. Robbery is the one other category worth watching: up 36.4% year-over-year (15 incidents vs. 11), though the raw counts remain small. Burglary, aggravated assault, and motor vehicle theft all ran below or near their prior-year levels without crossing a signal threshold.
Notable signals 1
Vandalism
The past 12 months saw 158 incidents — about 93% above the 82 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.
- Vandalism is climbing.
The trailing 12-month count is 158, up 72% from 92 the year before. If the trend holds another quarter, it will pull the multi-year baseline up.
- Other Larceny has reset to a lower baseline.
The trailing 12-month count is 135, down 27% from 184 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 March 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 Hegewisch compares
Peer neighborhoods picked by closest 12-month vandalism 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 vandalism levels.”
Armour Square
154 incidents over the past 12 months — 4 below Hegewisch's 158.
Open page →Dunning
153 incidents over the past 12 months — 5 below Hegewisch's 158.
Open page →Avalon Park
152 incidents over the past 12 months — 6 below Hegewisch's 158.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Hegewisch, 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 SFPD's open dataset, mapped to 10 NIBRS-aligned categories, and aggregated to neighborhood × 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.