SPIKE · OTHER LARCENYJUNE 2026 BRIEFINGDENVER · 7.2K 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 COUNT06 2026 · 44
0408112-mo avg: 46.9
UNIVERSITY HILLSCITYWIDE TREND (RESCALED)+7% 12MO YOY
-27%MoM
+48%12mo YoY
563last 12mo
44this month
01 · TL;DR

University Hills had two tracked signals in June 2026, both pointing the same direction: other larceny is running well above its historical range, both as a single-month spike and as a structural shift over the trailing 12 months. One zero-event signal rounded out the month — no other category moved enough to register.

Other larceny stands at 563 incidents over the current 12 months, up 48.2% against the prior 12-month total of 380 — and the sustained-shift signal confirms this isn't a single noisy month but a multi-month departure from baseline. Robbery, aggravated assault, burglary, theft from vehicle, and motor vehicle theft all ran below their prior-year levels — robbery down 33.3%, aggravated assault and motor vehicle theft each down 40.0% — making other larceny the sole category pulling against an otherwise broad decline in University Hills crime.

1 spike1 sustained shift1 zero-event
02 · Notable signals

Notable signals 1

SPIKE · OTHER LARCENY

Other Larceny

The past 12 months saw 563 incidents — about 239% above the 166 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
2024-072026-06
Robberybelow threshold
2024-072026-06
Aggravated Assaultbelow threshold
2024-072026-06
Burglary-21%
2024-072026-06
Theft from Vehicle-10%
2024-072026-06
Other Larceny+48%
2024-072026-06
Motor Vehicle Theft-40%
2024-072026-06
Vandalism0%
2024-072026-06
Arsonbelow threshold
2024-072026-06
05 · Forecast

What next month likely looks like

Forecasts trained through June 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

JULY 2026
Most likely 4 next month — likely between 0 and 7.
+24% vs 12-month average (≈2.8)

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

JULY 2026
Most likely 1 next month — likely between 0 and 5.

Other Larceny

JULY 2026
Most likely 52 next month — likely between 37 and 66.
+10% vs 12-month average (≈46.9)

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

JULY 2026
Most likely 8 next month — likely between 2 and 14.
+42% vs 12-month average (≈5.6)

Vandalism

JULY 2026
Most likely 4 next month — likely between 0 and 9.
18% vs 12-month average (≈5.2)
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?

University Hillsdoesn'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.

University Hills historical spike-event spillover by crime category (3-month lookahead, adjacent neighborhoods via shared boundary).
CategorySpike eventsSame-category spillover
Other larceny2— too few

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.

shopliftitemsdrugbusinessforcebldgpartssimpletrespassingbicyclefraudinjurethreatsorderdisturbingpeacetelephonecomputergraffitirestrainingsellharassmentmailsaggravatedinterference
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
013426812am6am12pm6pm11pm

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

DAY OF WEEK · ALL CATEGORIES
0256513MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
0184369JanFebMarAprMayJunJulAugSepOctNovDec
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.