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.
September 2026 in University District was defined by broad, sustained property crime declines rather than any single acute signal. Theft from vehicle, other larceny, motor vehicle theft, burglary, and robbery all ran below their prior 12-month totals across the trailing year. The one anomaly worth naming is structural absence: homicide registered as a zero-event signal, meaning the category produced no incidents in the tracked window.
Theft from vehicle is the largest mover in absolute terms, 507 incidents over the current 12 months against 599 in the prior year, a 15.4% reduction. Burglary and other larceny followed similar trajectories, down 6.9% and 9.0% respectively. Aggravated assault is the one category running above its prior-year pace, up 13.6% to 92 incidents, and vandalism is essentially flat at 264 vs. 260. Every other tracked category was within or below its prior-year 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.
No sustained shifts surfaced this month.
What next month likely looks like
Forecasts trained through September 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 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.”
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.