DROP · BURGLARYAPRIL 2026 BRIEFINGSEATTLE · 30.6K residents

Lake City Crime Rate Trends — Seattle

Lake City is a far-northeast neighborhood organized around Lake City Way NE, the historic primary route to Bothell and points north. Predominantly mid-century single-family homes and apartment buildings, with the Lake City Library and Civic Core area at 125th and 28th.

BURGLARY · 24-MO COUNT04 2026 · 22
0183612-mo avg: 15.4
LAKE CITYCITYWIDE TREND (RESCALED)-6% 12MO YOY
+16%MoM
-20%12mo YoY
185last 12mo
22this month
01 · TL;DR

Four signals surfaced in Lake City this April — one single-month below-trend move and three sustained structural shifts, all pointing in the same direction. The shape of the month is broadly downward: every tracked category shows a lower 12-month total than the year before, and the sustained-shift signals confirm this isn't noise from one quiet month.

Burglary is the standout single-month signal, with 185 incidents over the current 12 months against a baseline of 283.56 — down 20.3% year-over-year. Aggravated assault and theft from vehicle are both registered as sustained shifts downward: aggravated assault is at 61 incidents vs. 99 the prior year (down 38.4%), and theft from vehicle sits at 261 vs. 348 (down 25.0%). The remaining tracked categories — robbery, motor vehicle theft, vandalism, and other larceny — all show lower 12-month totals as well, and none crossed the anomaly threshold, meaning they're declining within expected range rather than breaking out.

1 drop3 sustained shifts
02 · Notable signals

Notable signals 1

DROP · BURGLARY

Burglary

The past 12 months saw 185 incidents — about 35% below the 284 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-30%
2024-052026-04
Aggravated Assault-38%
2024-052026-04
Sexual Assaultbelow threshold
2024-052026-04
Burglary-20%
2024-052026-04
Theft from Vehicle-25%
2024-052026-04
Other Larceny-9%
2024-052026-04
Motor Vehicle Theft-45%
2024-052026-04
Vandalism-22%
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 19 next month — likely between 4 and 31.
+20% vs 12-month average (≈15.4)

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 21 next month — likely between 7 and 35.
+73% vs 12-month average (≈11.9)

Other Larceny

MAY 2026
Most likely 18 next month — likely between 7 and 30.
+8% vs 12-month average (≈17.1)

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 32 next month — likely between 17 and 49.
+48% vs 12-month average (≈21.8)

Vandalism

MAY 2026
Most likely 13 next month — likely between 3 and 22.
+6% vs 12-month average (≈12.2)
06 · Context & comps

How Lake City compares

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

SPATIAL SPILLOVER · NEW

Do crime spikes here spill over to adjacent neighborhoods?

When Lake City has spiked motor vehicle theft historically (12 events on record), an adjacent neighborhood spiked the same category within 3 months 75% of the time. The strongest-travelling categories sit at the top of the table.

Lake City historical spike-event spillover by crime category (3-month lookahead, adjacent neighborhoods via shared boundary).
CategorySpike eventsSame-category spillover
Motor vehicle theft1275%

Each row shows Lake City's historical spike events for that category, and how often any of its 2 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 Lake City, excluding generic crime taxonomy. Useful as texture — what kinds of specifics show up here that don't show up elsewhere.

breakingenteringdestructionnibrsreportablesimpleaccessoriespartsaggravatedfraudbuildingautomatedcardcreditmachinetellerconfidencefalsegamepretensesswindleintimidationidentitydrivinginfluence
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
07241,44812am6am12pm6pm11pm

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

DAY OF WEEK · ALL CATEGORIES
09411,882MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
05511,101JanFebMarAprMayJunJulAugSepOctNovDec
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.