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.
Four categories moved in University this April — one spike, two one-month drops, and one sustained shift. The dominant signal is a structural rise in other larceny running against a broad property-crime decline everywhere else.
Other larceny is up 13.8% over the prior 12 months, 140 incidents against a baseline mean of 88.34 — the lone category moving in the wrong direction this period. Motor vehicle theft and burglary both ran below trend, and the 12-month totals back that up: motor vehicle theft is down 44.6% year-over-year (31 vs 56), burglary down 43.2% (21 vs 37). Robbery and theft from vehicle are also lower on a 12-month basis; aggravated assault is flat. The structural picture is broadly improving across violent and property crime — other larceny is the outlier.
Notable signals 3
Other Larceny
The past 12 months saw 140 incidents — about 58% above the 88 average from prior years.
Motor Vehicle Theft
The past 12 months saw 31 incidents — about 64% below the 87 average from prior years.
Burglary
The past 12 months saw 21 incidents — about 52% below the 44 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.
- Motor Vehicle Theft has reset to a lower baseline.
The trailing 12-month count is 31, down 45% from 56 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.
Theft from Vehicle
Vandalism
How University compares
Peer neighborhoods picked by closest 12-month other larceny 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 other larceny levels.”
East Colfax
140 incidents over the past 12 months — 0 below University's 140.
Open page →Cheesman Park
138 incidents over the past 12 months — 2 below University's 140.
Open page →Berkeley
137 incidents over the past 12 months — 3 below University's 140.
Open page →Do crime spikes here spill over to adjacent neighborhoods?
When University has spiked other larceny historically (15 events on record), an adjacent neighborhood spiked the same category within 3 months 73.3% of the time. The strongest-travelling categories sit at the top of the table.
| Category | Spike events | Same-category spillover |
|---|---|---|
| Other larceny | 15 | 73.3% |
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.