SPIKE · SEXUAL ASSAULTAPRIL 2026 BRIEFINGCHICAGO · 13.8K residents

Armour Square Crime Rate Trends — Chicago

Armour Square is a Near South Side community area that includes Chinatown's Wentworth Avenue commercial strip and the Guaranteed Rate Field stadium grounds. Named for Philip Armour and the meatpacking industry that once dominated the area; bordered by the Dan Ryan Expressway to the west and the South Branch of the Chicago River to the east.

SEXUAL ASSAULT · 24-MO COUNT04 2026 · 2
02512-mo avg: 2.2
ARMOUR SQUARECITYWIDE TREND (RESCALED)-0% 12MO YOY
0%MoM
+420%12mo YoY
26last 12mo
2this month
01 · TL;DR

Three categories moved in Armour Square this April — one fresh spike and two structural shifts pulling in opposite directions. The spike is sexual assault, a one-month above-trend signal against a 12-month total that has climbed far above its prior baseline. The two sustained shifts tell a split story: robbery has been trending down for months while vandalism has been trending up, making this a neighborhood with a cross-cutting structural pattern rather than a uniform direction.

Sexual assault is the lead signal: 26 incidents over the trailing 12 months against a prior-year total of 5, a 420.0% change year-over-year. Robbery sits at 57 incidents over the current 12 months versus 100 in the prior year, down 43.0% — a multi-month structural decline. Vandalism runs the other way, 148 incidents versus 106 in the prior year, up 39.6%, and that shift has persisted long enough to register as structural rather than noise. Everything else — burglary, motor vehicle theft, aggravated assault — came in within range.

1 spike2 sustained shifts
02 · Notable signals

Notable signals 1

SPIKE · SEXUAL ASSAULT

Sexual Assault

The past 12 months saw 26 incidents — about 339% above the 6 average from prior years.

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-43%
2024-052026-04
Aggravated Assault+3%
2024-052026-04
Sexual Assault+420%
2024-052026-04
Burglary-9%
2024-052026-04
Other Larceny+11%
2024-052026-04
Motor Vehicle Theft+6%
2024-052026-04
Vandalism+40%
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

MAY 2026
Most likely 2 next month — likely between 0 and 6.
13% vs 12-month average (≈2.6)

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 15.
+15% vs 12-month average (≈7.8)

Other Larceny

MAY 2026
Most likely 22 next month — likely between 10 and 37.
17% vs 12-month average (≈26.9)

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 11 next month — likely between 4 and 19.
12% vs 12-month average (≈12.3)
06 · Context & comps

How Armour Square compares

Peer neighborhoods picked by closest 12-month sexual assault 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 sexual assault levels.”

SPATIAL SPILLOVER · NEW

Do crime spikes here spill over to adjacent neighborhoods?

Armour Squaredoesn'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.

Armour Square historical spike-event spillover by crime category (3-month lookahead, adjacent neighborhoods via shared boundary).
CategorySpike eventsSame-category spillover
Sexual assault3— too few

Each row shows Armour Square's historical spike events for that category, and how often any of its 7 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 Armour Square, excluding generic crime taxonomy. Useful as texture — what kinds of specifics show up here that don't show up elsewhere.

simpleaggravatedweapondomestichandgundangerousfraudunlawfulretailstrongfinancialidentitypossessionbuildingconfidenceforciblegamelandcardarmedcuttinginstrumentknifefeetfists
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
019639212am6am12pm6pm11pm

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

DAY OF WEEK · ALL CATEGORIES
0466932MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
0303606JanFebMarAprMayJunJulAugSepOctNovDec
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.