Pullman Crime Rate Trends — Chicago
Pullman is a Far South Side neighborhood developed in 1880 by George Pullman as a planned company town for his Pullman Palace Car Company workers. The historic core is now the Pullman National Historical Park, with rowhouses and the original Hotel Florence; bordered by the Bishop Ford Expressway and the Calumet rail corridor.
March 2026 produced a single signal in Pullman — one sustained shift in motor vehicle theft, with no spikes, drops, or rare events across any other tracked category. The month's shape is narrow: one structural move in one category, everything else within range.
Motor vehicle theft is down 41.6% against the prior 12-year period — 59 incidents in the current 12 months against 101 in the year before — a multi-month structural decline, not a one-month dip. Robbery is also lower over the trailing year, down 38.5% (8 incidents vs. 13), and other larceny has fallen 18.4% to 249 from 305, though neither crossed the threshold for a formal signal this month. Burglary moved in the opposite direction, up 26.3% to 24 incidents, but again did not register as a signal.
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.
- Motor Vehicle Theft has reset to a lower baseline.
The trailing 12-month count is 59, down 42% from 101 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 Pullman compares
Peer neighborhoods picked by closest 12-month motor vehicle theft 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 motor vehicle theft levels.”
Fuller Park
61 incidents over the past 12 months — 2 above Pullman's 59.
Open page →McKinley Park
61 incidents over the past 12 months — 2 above Pullman's 59.
Open page →North Park
61 incidents over the past 12 months — 2 above Pullman's 59.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Pullman, 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.