ZERO EVENT · HOMICIDEAPRIL 2026 BRIEFINGSEATTLE · 55.7K residents

Downtown Crime Rate Trends — Seattle

Downtown Seattle is the central business district fronting Elliott Bay between Belltown and Pioneer Square, anchored by Pike Place Market, the Seattle waterfront, and the central Link light rail tunnel. Includes the retail core along Pine and Pike, the financial district, and the convention-center spine.

HOMICIDE · 24-MO COUNT04 2026 · 0
01112-mo avg: 0.0
DOWNTOWNCITYWIDE TREND (RESCALED)-46% 12MO YOY
MoM
12mo YoY
0last 12mo
0this month
01 · TL;DR

April 2026 was a structurally mixed month in Downtown Seattle, with no single-month anomalies surfacing across any tracked category. The one signal of note is a zero-event: homicide recorded no incidents in the current window, a rare absence in a high-volume urban core.

Across the 12-month totals, the picture divides cleanly. Theft from vehicle is down 12.6% against the prior year — 1,772 incidents vs. 2,027 — and vandalism is down 8.5% (1,126 vs. 1,230), both representing meaningful sustained movement. Running the other direction: other larceny is up 11.8% (1,799 vs. 1,609), sexual assault is up 75.0% on a small base (21 vs. 12), and arson is up 23.5% (42 vs. 34). Robbery, motor vehicle theft, and aggravated assault are all within a few percentage points of last year's pace.

1 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
2024-052026-04
Robbery+7%
2024-052026-04
Aggravated Assault-4%
2024-052026-04
Sexual Assault+75%
2024-052026-04
Burglary-4%
2024-052026-04
Theft from Vehicle-13%
2024-052026-04
Other Larceny+12%
2024-052026-04
Motor Vehicle Theft+5%
2024-052026-04
Vandalism-9%
2024-052026-04
Arson+24%
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

MAY 2026
Most likely 3 next month — likely between 0 and 7.
5% vs 12-month average (≈3.5)

Burglary

MAY 2026
Most likely 111 next month — likely between 65 and 166.
+5% vs 12-month average (≈105.6)

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 55 next month — likely between 37 and 73.
+3% vs 12-month average (≈53.4)

Other Larceny

MAY 2026
Most likely 95 next month — likely between 2 and 190.
36% vs 12-month average (≈149.9)

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.

Theft from Vehicle

MAY 2026
Most likely 142 next month — likely between 51 and 237.
4% vs 12-month average (≈147.7)

Vandalism

MAY 2026
Most likely 112 next month — likely between 77 and 146.
+20% vs 12-month average (≈93.8)
06 · Context & comps

How Downtown compares

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

SPATIAL SPILLOVER · NEW

Do crime spikes here spill over to adjacent neighborhoods?

Downtowndoesn'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.

Downtown 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 Downtown'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 Seattle); 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 Downtown, excluding generic crime taxonomy. Useful as texture — what kinds of specifics show up here that don't show up elsewhere.

nibrsreportablebreakingenteringdestructiondrugnarcoticsimpleaggravatedbuildingshopliftingaccessoriespartsweaponfraudmachineautomatedcardcredittellerdrivinginfluenceequipmentconfidencefalse
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
03,0886,17512am6am12pm6pm11pm

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

DAY OF WEEK · ALL CATEGORIES
05,92411,847MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
03,3266,653JanFebMarAprMayJunJulAugSepOctNovDec
08 · Methodology

How we built this page

Data → Anomalies → Forecast → Page

Incident data is pulled from SPD's Crime Data feed on Seattle Open Data, 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.