SUSTAINED DROP · MOTOR VEHICLE THEFTAPRIL 2026 BRIEFINGSEATTLE · 41.5K residents

Beacon Hill Crime Rate Trends — Seattle

Beacon Hill is a long ridge running south from the International District, anchored by the Beacon Hill Link light rail station and Jefferson Park atop the hill. Mostly single-family bungalows and craftsman homes on a tight grid, with Beacon Avenue South as the spine commercial corridor.

MOTOR VEHICLE THEFT · 24-MO COUNT04 2026 · 34
0244812-mo avg: 22.3
BEACON HILLCITYWIDE TREND (RESCALED)-17% 12MO YOY
+89%MoM
-26%12mo YoY
267last 12mo
34this month
01 · TL;DR

Beacon Hill's April 2026 briefing is defined by structural decline across vehicle-related property crime, not a single month's noise. Two categories registered sustained shifts — both pointing downward — against an otherwise stable backdrop. The overall picture is a neighborhood where property crime volumes have been compressing over multiple years.

Theft from vehicle and motor vehicle theft are both sustained-shift signals, each running well below their prior-year baselines: theft from vehicle is down 32.1% over the trailing 12 months (344 incidents vs. 507), and motor vehicle theft is down 26.2% (267 vs. 362). Every other tracked category fell within normal range this month — aggravated assault is the one counter-trend, up 7.9% year-over-year at 123 incidents, but it did not cross a signal threshold.

2 sustained shifts
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-19%
2024-052026-04
Aggravated Assault+8%
2024-052026-04
Sexual Assaultbelow threshold
2024-052026-04
Burglary-18%
2024-052026-04
Theft from Vehicle-32%
2024-052026-04
Other Larceny-24%
2024-052026-04
Motor Vehicle Theft-26%
2024-052026-04
Vandalism-18%
2024-052026-04
Arson+63%
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 23 next month — likely between 12 and 34.
+24% vs 12-month average (≈18.4)

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 24 next month — likely between 8 and 40.
+6% vs 12-month average (≈22.3)

Other Larceny

MAY 2026
Most likely 33 next month — likely between 16 and 48.
+12% vs 12-month average (≈29.1)

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 28 next month — likely between 11 and 45.
1% vs 12-month average (≈28.7)

Vandalism

MAY 2026
Most likely 24 next month — likely between 16 and 34.
+34% vs 12-month average (≈18.3)
06 · Context & comps

How Beacon Hill compares

Peer neighborhoods picked by closest 12-month motor vehicle theft 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 motor vehicle theft levels.”

SPATIAL SPILLOVER · NEW

Do crime spikes here spill over to adjacent neighborhoods?

When Beacon Hill has spiked robbery historically (5 events on record), an adjacent neighborhood spiked the same category within 3 months 100% of the time. The strongest-travelling categories sit at the top of the table.

Beacon Hill historical spike-event spillover by crime category (3-month lookahead, adjacent neighborhoods via shared boundary).
CategorySpike eventsSame-category spillover
Vandalism90%
Robbery5100%
Motor vehicle theft3— too few

Each row shows Beacon Hill's historical spike events for that category, and how often any of its 4 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 Beacon Hill, excluding generic crime taxonomy. Useful as texture — what kinds of specifics show up here that don't show up elsewhere.

nibrsreportablebreakingenteringdestructionaccessoriespartsaggravatedsimpleshopliftingdrivinginfluenceweaponfrauddrugautomatedbuildingcardcreditmachinetellernarcoticconfidencefalsegame
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
09101,81912am6am12pm6pm11pm

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

DAY OF WEEK · ALL CATEGORIES
01,4312,862MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
08621,724JanFebMarAprMayJunJulAugSepOctNovDec
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.