SPIKE · OTHER LARCENYSEPTEMBER 2026 BRIEFINGDENVER · 9.2K residents

Berkeley Crime Rate Trends — Denver

Berkeley is a northwest Denver neighborhood centered on Tennyson Street between West 38th and West 52nd Avenues, named after the now-vanished Berkeley Lake. The Tennyson commercial strip is a walkable mix of restaurants and shops; the side streets are early-20th-century bungalows and Denver Squares.

OTHER LARCENY · 24-MO COUNT09 2026 · 16
0122312-mo avg: 12.3
BERKELEYCITYWIDE TREND (RESCALED)+5% 12MO YOY
+129%MoM
+36%12mo YoY
147last 12mo
16this month
01 · TL;DR

September 2026 produced a single notable signal in Berkeley: other larceny registered a spike, the only category this month that moved outside its expected range. Every other tracked category stayed within normal bounds.

Other larceny stands out because it has climbed steadily over the trailing 12 months, 147 incidents against 108 in the prior year, a 36.1% increase. Burglary and theft from vehicle also rose year-over-year, up 16.2% and 12.0% respectively, suggesting a broader drift upward in property crime. On the other side, violent categories moved the other way: aggravated assault is down 41.2% over 12 months, 10 incidents vs. 17, and motor vehicle theft fell 35.4%.

1 spike
02 · Notable signals

Notable signals 1

SPIKE · OTHER LARCENY

Other Larceny

The past 12 months saw 147 incidents — about 30% above the 113 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
2024-102026-09
Robberybelow threshold
2024-102026-09
Aggravated Assault-41%
2024-102026-09
Burglary+16%
2024-102026-09
Theft from Vehicle+12%
2024-102026-09
Other Larceny+36%
2024-102026-09
Motor Vehicle Theft-35%
2024-102026-09
Vandalism+13%
2024-102026-09
Arsonbelow threshold
2024-102026-09
05 · Forecast

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

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

OCTOBER 2026
Most likely 6 next month — likely between 1 and 11.
−9% vs 12-month average (≈6.6)

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

OCTOBER 2026
Most likely 3 next month — likely between 0 and 7.
+11% vs 12-month average (≈2.6)

Other Larceny

OCTOBER 2026
Most likely 10 next month — likely between 4 and 16.
−17% vs 12-month average (≈12.3)

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

OCTOBER 2026
Most likely 5 next month — likely between 0 and 12.
−40% vs 12-month average (≈7.8)

Vandalism

OCTOBER 2026
Most likely 3 next month — likely between 0 and 7.
−33% vs 12-month average (≈5.1)
06 · Context & comps

How Berkeley 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?

Berkeleydoesn'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.

Berkeley historical spike-event spillover by crime category (3-month lookahead, adjacent neighborhoods via shared boundary).
CategorySpike eventsSame-category spillover
Other larceny1— too few

Each row shows Berkeley's historical spike events for that category, and how often any of its 5 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 Berkeley, excluding generic crime taxonomy. Useful as texture — what kinds of specifics show up here that don't show up elsewhere.

itemsforcebldgresidencepartsbusinessshopliftbicycledrugorderfraudsimpletrespassingaggravatedcomputerrestrainingcourtinjureliquorpossthreatsdischargeparaphernaliapolicepossess
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
08717512am6am12pm6pm11pm

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

DAY OF WEEK · ALL CATEGORIES
0226452MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
0148296JanFebMarAprMayJunJulAugSepOctNovDec
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.