DROP · ROBBERYAPRIL 2026 BRIEFINGCHICAGO · 54.4K residents

Chicago Lawn Crime Rate Trends — Chicago

Chicago Lawn — also known as Marquette Park — is a Southwest Side neighborhood organized around 63rd Street and California Avenue. Anchored by Marquette Park itself, one of the largest parks on the South Side, with predominantly bungalow housing on a tight grid.

ROBBERY · 24-MO COUNT04 2026 · 4
0132512-mo avg: 8.6
CHICAGO LAWNCITYWIDE TREND (RESCALED)-34% 12MO YOY
-56%MoM
-43%12mo YoY
103last 12mo
4this month
01 · TL;DR

Three categories moved in Chicago Lawn this April — two one-month below-trend signals and one sustained structural shift. The overall shape is downward, concentrated in robbery and vandalism, with robbery carrying both a single-month drop and a longer-term structural signal.

Robbery is the most pronounced move: the trailing 12-month total sits at 103 incidents against a prior-year figure of 179, a 42.5% reduction. Vandalism also ran below trend this month, with 537 incidents over the current 12 months versus 575 in the year prior. Everything else — motor vehicle theft, aggravated assault, burglary — was within range and registered no signals.

2 drops1 sustained shift
02 · Notable signals

Notable signals 2

DROP · ROBBERY

Robbery

The past 12 months saw 103 incidents — about 50% below the 204 average from prior years.

DROP · VANDALISM

Vandalism

The past 12 months saw 537 incidents — about 15% below the 633 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-20%
2024-052026-04
Sexual Assault+21%
2024-052026-04
Burglary-20%
2024-052026-04
Other Larceny-18%
2024-052026-04
Motor Vehicle Theft-9%
2024-052026-04
Vandalism-7%
2024-052026-04
Arson-28%
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 7 next month — likely between 0 and 19.
23% vs 12-month average (≈9.4)

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 33 next month — likely between 13 and 53.
+29% vs 12-month average (≈25.3)

Other Larceny

MAY 2026
Most likely 59 next month — likely between 36 and 83.
+7% vs 12-month average (≈55.3)

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 52 next month — likely between 37 and 66.
+16% vs 12-month average (≈44.8)
06 · Context & comps

How Chicago Lawn compares

Peer neighborhoods picked by closest 12-month robbery 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 robbery levels.”

SPATIAL SPILLOVER · NEW

Do crime spikes here spill over to adjacent neighborhoods?

Chicago Lawndoesn'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.

Chicago Lawn historical spike-event spillover by crime category (3-month lookahead, adjacent neighborhoods via shared boundary).
CategorySpike eventsSame-category spillover
Aggravated assault1— too few

Each row shows Chicago Lawn's historical spike events for that category, and how often any of its 5 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 Chicago Lawn, excluding generic crime taxonomy. Useful as texture — what kinds of specifics show up here that don't show up elsewhere.

simpledomesticaggravatedhandgunpossessunlawfulweaponpossessiontelephoneretaildangerousharassmentcuttinginstrumentknifefraudfinancialidentityforciblecracklandorderprotectionviolatethreat
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
07181,43612am6am12pm6pm11pm

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

DAY OF WEEK · ALL CATEGORIES
01,7363,473MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
01,0472,094JanFebMarAprMayJunJulAugSepOctNovDec
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.