SUSTAINED DROP · MOTOR VEHICLE THEFTAPRIL 2026 BRIEFINGCHICAGO · 6.7K residents

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.

MOTOR VEHICLE THEFT · 24-MO COUNT04 2026 · 4
081612-mo avg: 4.8
PULLMANCITYWIDE TREND (RESCALED)-10% 12MO YOY
-43%MoM
-43%12mo YoY
58last 12mo
4this month
01 · TL;DR

April 2026 produced a single signal in Pullman: motor vehicle theft has shifted structurally downward, a sustained multi-month move rather than a one-month dip. Every other tracked category — robbery, aggravated assault, other larceny, vandalism — stayed within its expected range.

Motor vehicle theft is down 42.6% against the prior 12 months, the clearest directional move in the neighborhood this period. Other larceny also ran below its prior-year pace at 258 incidents vs. 296, and robbery edged down from 13 to 10 over the same window. On the other side, burglary rose from 19 to 27 incidents year-over-year — a 42.1% increase — but did not cross the anomaly threshold this month.

1 sustained shift
02 · Notable signals

Notable signals 0

Nothing notable surfaced this month — every category sits within normal range against its baseline.

03 · By category

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.

Homicidebelow threshold
2024-052026-04
Robbery-23%
2024-052026-04
Aggravated Assault-9%
2024-052026-04
Sexual Assault+100%
2024-052026-04
Burglary+42%
2024-052026-04
Other Larceny-13%
2024-052026-04
Motor Vehicle Theft-43%
2024-052026-04
Vandalism-5%
2024-052026-04
Arsonbelow threshold
2024-052026-04
05 · Forecast

What next month likely looks like

Forecasts trained through April 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

NO FORECAST

Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.

Arson

NO FORECAST

Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.

Burglary

NO FORECAST

Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.

Homicide

NO FORECAST

Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.

Motor Vehicle Theft

MAY 2026
Most likely 9 next month — likely between 3 and 14.
+78% vs 12-month average (≈4.8)

Other Larceny

MAY 2026
Most likely 24 next month — likely between 11 and 37.
+11% vs 12-month average (≈21.5)

Robbery

NO FORECAST

Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.

Sexual Assault

NO FORECAST

Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.

Vandalism

MAY 2026
Most likely 9 next month — likely between 3 and 15.
+4% vs 12-month average (≈8.8)
06 · Context & comps

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.”

SPATIAL SPILLOVER · NEW

Do crime spikes here spill over to adjacent neighborhoods?

Pullmandoesn't have enough spike history in any single category for a stable spillover rate yet (we want at least 5 events). The table below lists what we have.

Pullman historical spike-event spillover by crime category (3-month lookahead, adjacent neighborhoods via shared boundary).
CategorySpike eventsSame-category spillover
Other larceny2— too few

Each row shows Pullman's historical spike events for that category, and how often any of its 4 adjacent neighborhoods spiked the same category within the next 3 months. A high same-category rate suggests a shock that travels (e.g. theft crews moving across Chicago); a low rate means spikes here tend to be local to the neighborhood. Categories with fewer than 5 historical spike events are listed but their rates are suppressed.

07 · Patterns

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.

simpledomesticretailaggravatedhandguntelephonethreatunlawfulharassmentweaponfeetfistshandsinjuryfrauddangerouspossessionforciblefinancialidentityorderelectronicmeansbuildingcard
When does it happen?

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.

HOUR OF DAY · ALL CATEGORIES
013827612am6am12pm6pm11pm

Hour 0 is mildly inflated by reports without a known time defaulting to midnight — see methodology.

DAY OF WEEK · ALL CATEGORIES
0356713MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
0208417JanFebMarAprMayJunJulAugSepOctNovDec
08 · Methodology

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.