DROP · MOTOR VEHICLE THEFTMARCH 2026 BRIEFINGOAKLAND · 6.3K residents

Chinatown Crime Rate Trends — Oakland

Chinatown is a compact downtown neighborhood centered on 8th and Webster Streets, anchored by produce markets, restaurants, and Madison Square Park. One of the oldest continuously occupied Chinatowns in North America, immediately southeast of the Lake Merritt BART station.

MOTOR VEHICLE THEFT · 24-MO COUNT03 2026 · 3
0163212-mo avg: 8.1
CHINATOWNCITYWIDE TREND (RESCALED)-25% 12MO YOY
-73%MoM
-61%12mo YoY
97last 12mo
3this month
01 · TL;DR

Four categories moved in Chinatown this March — one below-trend drop and three sustained structural shifts. The structural picture is mixed: burglary and motor vehicle theft are both running well below their multi-year baselines, while other larceny and several other categories have moved durably higher. This is not a uniformly quiet neighborhood; it's one where different crime types are moving in opposite directions at the same time.

Motor vehicle theft is the most prominent single signal: 97 incidents over the current 12 months against a baseline mean of 218.95, a reduction of more than half. Burglary shows a similar structural drop — 67 incidents in the current 12 months versus 140 in the prior year, down 52.1%. Moving the other direction, other larceny has risen 33.8% year-over-year (305 vs. 228), and that shift registers as sustained, not a one-month move. The remaining categories — robbery down 25.4%, aggravated assault up 28.0% — were within tracked range but add to a picture of a neighborhood in which property crime is diverging sharply by type.

1 drop3 sustained shifts
02 · Notable signals

Notable signals 1

DROP · MOTOR VEHICLE THEFT

Motor Vehicle Theft

The past 12 months saw 97 incidents — about 56% below the 219 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-25%
2024-042026-03
Robbery-25%
2024-042026-03
Aggravated Assault+28%
2024-042026-03
Sexual Assault+14%
2024-042026-03
Burglary-52%
2024-042026-03
Theft from Vehicle+18%
2024-042026-03
Other Larceny+34%
2024-042026-03
Motor Vehicle Theft-61%
2024-042026-03
Vandalism+16%
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 8 next month — likely between 0 and 15.
+35% vs 12-month average (≈5.6)

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

APRIL 2026
Most likely 12 next month — likely between 0 and 26.
+43% vs 12-month average (≈8.1)

Other Larceny

APRIL 2026
Most likely 20 next month — likely between 9 and 30.
22% vs 12-month average (≈25.4)

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 26 next month — likely between 6 and 46.
+1% vs 12-month average (≈26.1)

Vandalism

APRIL 2026
Most likely 7 next month — likely between 0 and 15.
41% vs 12-month average (≈11.2)
06 · Context & comps

How Chinatown compares

Peer neighborhoods picked by closest 12-month motor vehicle theft 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 motor vehicle theft levels.”

07 · Patterns

Recurring local terms (last 12 months)

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

creditgrandpeacedisturbforcecustodydecreespousefirearmweaponlabormoneyterrorizedangerousfeetfistshandsstrongdeathforcibleintentunexplainedcourtobtaindate
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
029058112am6am12pm6pm11pm

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

DAY OF WEEK · ALL CATEGORIES
06091,219MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
0342684JanFebMarAprMayJunJulAugSepOctNovDec
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.