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.
April 2026 produced just one tracked signal in University District — a sustained structural shift in vandalism, down 25.6% against the prior 12 months. That single movement is the shape of this month: not a cluster of one-off swings, but evidence of a longer downward trend in one category against an otherwise in-range backdrop.
Vandalism is the standout, with 241 incidents over the current 12-month window against 324 in the year before — a gap that has persisted long enough to register as a structural shift rather than a quiet month. Property crime categories more broadly are running lower year-over-year: burglary is down 19.4% (387 vs. 480), theft from vehicle down 21.4% (535 vs. 681), and other larceny down 21.8% (435 vs. 556). Everything else this month fell within normal range.
Notable signals 0
Nothing notable surfaced this month — every category sits within normal range against its baseline.
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.
What's been quietly true for a year
Spikes get attention. Sustained shifts shape policy. These are multi-quarter patterns where the past 12-month total differs meaningfully from the year before — they often precede the baseline resetting.
- Vandalism has reset to a lower baseline.
The trailing 12-month count is 241, down 26% from 324 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
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
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Arson
Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.
Burglary
Homicide
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Motor Vehicle Theft
Other Larceny
Robbery
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Sexual Assault
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Theft from Vehicle
Vandalism
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.”
Greater Duwamish
251 incidents over the past 12 months — 10 above University District's 241.
Open page →West Seattle
228 incidents over the past 12 months — 13 below University District's 241.
Open page →Northeast
227 incidents over the past 12 months — 14 below University District's 241.
Open page →Do crime spikes here spill over to adjacent neighborhoods?
When University District has spiked motor vehicle theft 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.
| Category | Spike events | Same-category spillover |
|---|---|---|
| Motor vehicle theft | 5 | 100% |
Each row shows University District'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.
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.
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.
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.