DROP · ROBBERYMARCH 2026 BRIEFINGOAKLAND · 6.1K residents

Uptown Crime Rate Trends — Oakland

Uptown is a downtown-adjacent neighborhood centered on the 19th Street BART station and the Telegraph Avenue commercial corridor between 17th and 27th Streets. Anchored by the historic Fox and Paramount theaters and a concentration of art deco and mid-century commercial buildings.

ROBBERY · 24-MO COUNT03 2026 · 3
03712-mo avg: 1.8
UPTOWNCITYWIDE TREND (RESCALED)-39% 12MO YOY
0%MoM
-48%12mo YoY
21last 12mo
3this month
01 · TL;DR

Five categories moved in Uptown this March — three ran below trend as one-month drops and two registered as sustained structural shifts. The overall shape is broadly downward, particularly across property crime, with no spikes or rare-event signals in the mix.

Robbery leads the drop signals: 21 incidents over the current 12 months against a baseline of 51.58, and down 47.5% from the prior year's 40. Vandalism and Burglary also ran below trend, with vandalism off 50.0% year-over-year (94 vs. 188) and burglary down 28.8% (37 vs. 52). The two sustained-shift signals indicate these aren't one-month dips — the structural direction across property categories has been downward for multiple months.

3 drops2 sustained shifts
02 · Notable signals

Notable signals 3

DROP · ROBBERY

Robbery

The past 12 months saw 21 incidents — about 59% below the 52 average from prior years.

DROP · VANDALISM

Vandalism

The past 12 months saw 94 incidents — about 74% below the 357 average from prior years.

DROP · BURGLARY

Burglary

The past 12 months saw 37 incidents — about 53% below the 78 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.

Homicide+74%
2024-042026-03
Robbery-48%
2024-042026-03
Aggravated Assault+50%
2024-042026-03
Sexual Assault-21%
2024-042026-03
Burglary-29%
2024-042026-03
Theft from Vehicle-23%
2024-042026-03
Other Larceny-25%
2024-042026-03
Motor Vehicle Theft-20%
2024-042026-03
Vandalism-50%
2024-042026-03
Arsonbelow threshold
2024-042026-03
05 · Forecast

What next month likely looks like

Forecasts trained through March 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

APRIL 2026
Most likely 3 next month — likely between 0 and 8.
7% vs 12-month average (≈3.1)

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

APRIL 2026
Most likely 15 next month — likely between 6 and 24.
+32% vs 12-month average (≈11.2)

Other Larceny

APRIL 2026
Most likely 18 next month — likely between 4 and 31.
+28% vs 12-month average (≈13.7)

Robbery

NO FORECAST

Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.

Sexual Assault

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

APRIL 2026
Most likely 23 next month — likely between 0 and 60.
+14% vs 12-month average (≈19.9)

Vandalism

APRIL 2026
Most likely 11 next month — likely between 0 and 30.
+35% vs 12-month average (≈7.8)
06 · Context & comps

How Uptown compares

Peer neighborhoods picked by closest 12-month robbery 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 robbery levels.”

SPATIAL SPILLOVER · NEW

Do crime spikes here spill over to adjacent neighborhoods?

Uptowndoesn'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.

Uptown historical spike-event spillover by crime category (3-month lookahead, adjacent neighborhoods via shared boundary).
CategorySpike eventsSame-category spillover
Homicide3— too few

Each row shows Uptown's historical spike events for that category, and how often any of its 6 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 Oakland); 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 Uptown, excluding generic crime taxonomy. Useful as texture — what kinds of specifics show up here that don't show up elsewhere.

spousegrandforceterrorizedeathfirearminflictunexplainedinjuryweapondatepeacecohabitantcorporaldangerousdisturbcourtintentthreatedthreatsmailorderconsentthreattrespass
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
031763412am6am12pm6pm11pm

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

DAY OF WEEK · ALL CATEGORIES
06371,274MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
0359717JanFebMarAprMayJunJulAugSepOctNovDec
08 · Methodology

How we built this page

Data → Anomalies → Forecast → Page

Incident data is pulled from OPD's CrimeWatch feed on Oakland Open Data, mapped to 10 NIBRS-aligned categories, and aggregated to 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.