SUSTAINED DROP · VANDALISMMARCH 2026 BRIEFINGSEATTLE · 30.8K residents

University District Crime Rate Trends — Seattle

The University District is the neighborhood surrounding the University of Washington's main campus, organized around University Way NE ("the Ave") and the U District Link light rail station. Mixed student housing, mid-rise apartments, and the UW campus itself running east to Lake Washington.

VANDALISM · 24-MO COUNT03 2026 · 25
0244812-mo avg: 20.7
UNIVERSITY DISTRICTCITYWIDE TREND (RESCALED)-11% 12MO YOY
+32%MoM
-26%12mo YoY
248last 12mo
25this month
01 · TL;DR

University District had a structurally quiet March 2026. One category — vandalism — registered a sustained shift downward, meaning the decline isn't a single off month but a multi-month structural change in volume. A zero-event signal rounded out the count, and every other tracked category stayed within range.

Vandalism is the month's defining movement: 248 incidents over the current 12 months against 334 in the prior year, down 25.7%. That's a structural reset, not noise. Elsewhere, burglary is also running well below its prior-year level (380 vs. 501, down 24.2%) and theft from vehicle is down 20.1% — neither crossed the signal threshold this month, but both contribute to a broadly lower property-crime baseline across the neighborhood. Aggravated assault moved in the opposite direction, 93 incidents against 86 a year ago, up 8.1%, though it did not register as a signal either.

1 sustained shift1 zero-event
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
2024-042026-03
Robbery-10%
2024-042026-03
Aggravated Assault+8%
2024-042026-03
Sexual Assaultbelow threshold
2024-042026-03
Burglary-24%
2024-042026-03
Theft from Vehicle-20%
2024-042026-03
Other Larceny-18%
2024-042026-03
Motor Vehicle Theft-3%
2024-042026-03
Vandalism-26%
2024-042026-03
Arsonbelow threshold
2024-042026-03
05 · Forecast

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

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

APRIL 2026
Most likely 39 next month — likely between 24 and 55.
+24% vs 12-month average (≈31.7)

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

APRIL 2026
Most likely 28 next month — likely between 15 and 40.
+7% vs 12-month average (≈25.7)

Other Larceny

APRIL 2026
Most likely 38 next month — likely between 18 and 60.
+3% vs 12-month average (≈37.4)

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.

Theft from Vehicle

APRIL 2026
Most likely 48 next month — likely between 25 and 71.
+6% vs 12-month average (≈45.1)

Vandalism

APRIL 2026
Most likely 24 next month — likely between 10 and 38.
+16% vs 12-month average (≈20.7)
06 · Context & comps

How University District 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.”

07 · Patterns

Recurring local terms (last 12 months)

Top terms in incident descriptions for University District, excluding generic crime taxonomy. Useful as texture — what kinds of specifics show up here that don't show up elsewhere.

breakingenteringdestructionnibrsreportableaccessoriespartsbuildingsimpleaggravatedfraudautomatedcardcreditmachinetellerdrugshopliftingintimidationidentityweaponnarcoticconfidencefalsegame
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
01,0882,17712am6am12pm6pm11pm

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

DAY OF WEEK · ALL CATEGORIES
01,6263,253MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
09821,964JanFebMarAprMayJunJulAugSepOctNovDec
08 · Methodology

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.