University Crime Rate Trends — Denver
University is the south-central Denver neighborhood organized around the University of Denver campus, between South University Boulevard and South Colorado Boulevard. The campus dominates the geography; the surrounding streets are a mix of student housing, mid-century single-family homes, and the Asbury and Evans Avenue commercial strips.
Two signals surfaced in University this month, one single-month drop and one structural sustained shift, against an otherwise quiet backdrop. The shape of September 2026 is a neighborhood where the dominant property crime categories are moving broadly downward, some for a single month, one over a longer multi-year arc.
Motor vehicle theft is the stronger of the two signals: 13 incidents in the current 12-month window against 46 in the prior year, a 71.7% reduction. Theft from vehicle is the sustained-shift story, down 39.5% over the same horizon, 46 incidents vs. 76, a structural move rather than a single quiet month. Everything else, robbery, aggravated assault, vandalism, burglary, and other larceny, fell within normal range, with burglary the one category running above its prior-year pace, up 21.4% on small absolute counts (34 vs. 28).
Notable signals 1
Motor Vehicle Theft
The past 12 months saw 13 incidents — about 84% below the 81 average from prior years.
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.
- Theft from Vehicle has reset to a lower baseline.
The trailing 12-month count is 46, down 40% from 76 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 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.
Theft from Vehicle
Vandalism
How University 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.”
Auraria
13 incidents over the past 12 months — 0 below University's 13.
Open page →Montclair
15 incidents over the past 12 months — 2 above University's 13.
Open page →Rosedale
11 incidents over the past 12 months — 2 below University's 13.
Open page →Do crime spikes here spill over to adjacent neighborhoods?
Universitydoesn'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.
| Category | Spike events | Same-category spillover |
|---|---|---|
| Other larceny | 1 | — too few |
Each row shows University'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 Denver); 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, 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 Denver Open Data — DPD's NIBRS-coded crime offenses on ArcGIS Hub — mapped to 9 NIBRS-aligned categories (sexual assault is excluded because DPD redacts victim-bearing rows from the public feed). The feed publishes a 5-year rolling window so the analysis baseline starts at 2021-01. Aggregated to statistical 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.