SPIKE · OTHER LARCENYJUNE 2026 BRIEFINGDENVER · 9.0K residents

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.

OTHER LARCENY · 24-MO COUNT06 2026 · 10
0112212-mo avg: 11.9
UNIVERSITYCITYWIDE TREND (RESCALED)+7% 12MO YOY
-9%MoM
+12%12mo YoY
143last 12mo
10this month
01 · TL;DR

June 2026 in University produced two signals moving in opposite directions — an other-larceny spike and a motor vehicle theft drop — against an otherwise within-range month across all seven tracked categories.

Other larceny is the sharper of the two signals: the trailing 12-month total of 143 incidents sits well above the 90.56 baseline mean, and the category is up 11.7% against the prior year's 128 incidents. Motor vehicle theft moved the other way — down 45.7% year-over-year, 25 incidents against 46 in the prior 12 months. Burglary and theft from vehicle also continued multi-year declines (down 29.7% and 32.5% respectively), though neither crossed a signal threshold this month; everything else held close to prior-year levels.

1 spike1 drop
02 · Notable signals

Notable signals 2

SPIKE · OTHER LARCENY

Other Larceny

The past 12 months saw 143 incidents — about 58% above the 91 average from prior years.

DROP · MOTOR VEHICLE THEFT

Motor Vehicle Theft

The past 12 months saw 25 incidents — about 70% below the 84 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-30%
2024-072026-06
Theft from Vehicle-33%
2024-072026-06
Other Larceny+12%
2024-072026-06
Motor Vehicle Theft-46%
2024-072026-06
Vandalism-2%
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 1 and 7.
+77% vs 12-month average (≈2.2)

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 4 next month — likely between 0 and 9.
+107% vs 12-month average (≈2.1)

Other Larceny

JULY 2026
Most likely 10 next month — likely between 4 and 16.
12% vs 12-month average (≈11.9)

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 5 next month — likely between 0 and 11.
+13% vs 12-month average (≈4.3)

Vandalism

JULY 2026
Most likely 4 next month — likely between 0 and 9.
+12% vs 12-month average (≈3.9)
06 · Context & comps

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.”

SPATIAL SPILLOVER · NEW

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.

University 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'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.

07 · Patterns

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.

shopliftitemsbicycleforcepartssimplebldgfraudresidencetrespassingbusinessdruginjurethreatsdisturbingpeacetelephoneaggravatedorderrestrainingunauthmailsmenacingweapweapon
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
07615212am6am12pm6pm11pm

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

DAY OF WEEK · ALL CATEGORIES
0190381MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
0125251JanFebMarAprMayJunJulAugSepOctNovDec
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.