SPIKE · OTHER LARCENYAPRIL 2026 BRIEFINGDENVER · 6.9K residents

University Hills Crime Rate Trends — Denver

University Hills is a south Denver neighborhood between Yale Avenue and Hampden Avenue, organized around University Hills Plaza and South Colorado Boulevard. Predominantly mid-century single-family residential with the namesake shopping center and apartment-building corridors along Colorado.

OTHER LARCENY · 24-MO COUNT04 2026 · 42
0408112-mo avg: 44.2
UNIVERSITY HILLSCITYWIDE TREND (RESCALED)+8% 12MO YOY
-14%MoM
+48%12mo YoY
530last 12mo
42this month
01 · TL;DR

University Hills had two tracked signals in April 2026, both concentrated in other larceny. The month's shape is narrow: a single-month spike and a sustained structural shift in the same category, plus a zero-event signal, against an otherwise unremarkable backdrop across the remaining five tracked categories.

Other larceny is the category doing all the work. The trailing 12 months logged 530 incidents — up 48.0% against the prior 12 months' 358, and well above the multi-year baseline of 155.27 annual incidents. Robbery and burglary are both running lower year-over-year (down 42.9% and 29.4% respectively), and theft from vehicle is flat at 73 incidents in each period. The other larceny move is structural, not noise: the sustained-shift signal means the elevated volume has persisted across multiple months, not just April.

1 spike1 sustained shift1 zero-event
02 · Notable signals

Notable signals 1

SPIKE · OTHER LARCENY

Other Larceny

The past 12 months saw 530 incidents — about 241% above the 155 average from prior years.

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
Robberybelow threshold
2024-052026-04
Aggravated Assault+43%
2024-052026-04
Burglary-29%
2024-052026-04
Theft from Vehicle0%
2024-052026-04
Other Larceny+48%
2024-052026-04
Motor Vehicle Theft-31%
2024-052026-04
Vandalism-6%
2024-052026-04
Arsonbelow threshold
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 5 next month — likely between 1 and 8.
+50% vs 12-month average (≈3.0)

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 3 next month — likely between 0 and 7.
+69% vs 12-month average (≈2.0)

Other Larceny

MAY 2026
Most likely 47 next month — likely between 31 and 64.
+6% vs 12-month average (≈44.2)

Robbery

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 5 next month — likely between 0 and 11.
15% vs 12-month average (≈6.1)

Vandalism

MAY 2026
Most likely 7 next month — likely between 1 and 12.
+31% vs 12-month average (≈5.0)
06 · Context & comps

How University Hills 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.”

SPATIAL SPILLOVER · NEW

Do crime spikes here spill over to adjacent neighborhoods?

When University Hills has spiked other larceny historically (16 events on record), an adjacent neighborhood spiked the same category within 3 months 75% of the time. The strongest-travelling categories sit at the top of the table.

University Hills historical spike-event spillover by crime category (3-month lookahead, adjacent neighborhoods via shared boundary).
CategorySpike eventsSame-category spillover
Other larceny1675%

Each row shows University Hills's historical spike events for that category, and how often any of its 8 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.

07 · Patterns

Recurring local terms (last 12 months)

Top terms in incident descriptions for University Hills, excluding generic crime taxonomy. Useful as texture — what kinds of specifics show up here that don't show up elsewhere.

shopliftitemsbusinessforcedrugbldgtrespassingpartsbicycleordersimplefraudinjurethreatsrestrainingcomputerdisturbingpeaceaggravatedtelephonecrimesgraffitiharassmentmailsmenacing
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
012925912am6am12pm6pm11pm

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

DAY OF WEEK · ALL CATEGORIES
0247494MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
0167333JanFebMarAprMayJunJulAugSepOctNovDec
08 · Methodology

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.