Oakland · March 2026 briefing

Oakland Crime Rate Trends

Data sourced from the Oakland Police Department (OPD) Open Data portal and analyzed by Public Analyst.ai: 35 neighborhoods, 10 incident categories, twelve months of trailing comparison. Browse the rankings, scan the multi-year trends, or open a neighborhood-level breakdown.

Read methodologyUPDATED · AS OF 2026-03
136
tracked signals this month — across spikes, drops, sustained shifts, rare events.
-20.6%
overall city incident volume vs. trailing 12-month avg.
35
neighborhoods covered. Each gets its own page.
10
incident categories tracked, NIBRS-aligned.

Piedmont Pines other-larceny is the headline signal for March 2026 — a fresh spike that moves the category to the top of Oakland's rankings this month. The prior briefing lead, Millsmont homicide, remains in the top five and is worth watching, but homicide has now been the dominant bucket across recent months; other-larceny represents a category shift in what's driving the anomaly rankings.

Citywide volume is down 20.6% against the prior 12 months — 27,981 incidents versus 35,258 the year before. The signal mix leans heavily toward declines: 68 sustained-shift signals and 64 below-trend signals across 35 neighborhoods, against just 3 spikes and 1 streak break. Rockridge theft-from-vehicle and San Antonio robbery also surface in the top five, the latter running below trend.

The structural story for Oakland in March 2026 is a broad, sustained decline — 136 total signals with the overwhelming majority pointing downward. The Piedmont Pines other-larceny spike is new this month and breaks from that pattern, making it the one category to track as April data comes in. Millsmont homicide remains the persistent backdrop.

WHAT TO READ NEXT
Direct answers

Oakland Crime Frequently Asked Questions

Trailing 12 months vs the prior 12 months, computed from the same NIBRS-aligned categories used everywhere else on the page. Updated each March 2026 briefing.

Is crime in Oakland down?

Yes — citywide incident volume is 20.6% lower than the prior 12 months.

Across the trailing 12-month window we tracked 27,981 incidents in NIBRS-aligned categories, compared to 35,258 in the year before — down 7,277 incidents.

Is violent crime in Oakland down?

Yes — homicide, robbery, aggravated assault, and sexual assault are down 24.7% combined in the trailing 12 months.

That's 3,985 violent incidents in the past year against 5,291 in the prior year. See the by-category section below for the per-bucket breakdown.

Is property crime in Oakland down?

Yes — burglary, theft from vehicle, larceny, motor vehicle theft, and arson are down 19.4% combined in the trailing 12 months.

That's 20,998 property incidents in the past year against 26,047 in the prior year.

What are the safest neighborhoods to stay in Oakland?

  1. Upper Rockridge18.7 incidents per 1,000 residents
  2. Montclair24.9 incidents per 1,000 residents
  3. Piedmont Pines25.1 incidents per 1,000 residents

The three safest neighborhoods in Oakland, ranked by trailing-12-month incidents per 1,000 residents.

Computed as NIBRS-aligned trailing-12-month incident totals divided by the latest ACS 5-year residential population, expressed per 1,000 residents. Restricted to neighborhoods with at least 1,000 residents so park-only and industrial geographies — where visitor populations are not reflected in the residential denominator — are excluded.

Which neighborhood in Oakland saw the biggest crime drop?

Brookfield Village — 42.6% fewer incidents than the prior 12 months.

Brookfield Village logged 901 incidents in the trailing 12 months against 1,569 the year before.

Which neighborhood in Oakland saw the biggest crime increase?

Rockridge — 18.2% more incidents than the prior 12 months.

Rockridge logged 1,334 incidents in the trailing 12 months against 1,129 the year before.

City profile

The denominators behind the numbers

SOURCES · US CENSUS ACS 2024 · OAKLAND OPEN DATA · OPD
Geography
Land area55.9 mi²
Water area22.1 mi²
CoastlineBay frontage + Estuary
Elevation0–1,761 ft
Police beats57
Neighborhoods35 (analysis units)

Bay-fronting, hill-stacked city; the I-580 ridge and Highway 13 carve the flatlands from the hills, and major arterials (Telegraph, MacArthur, International) define most neighborhood boundaries.

Population
434,261
Density~7,769 / mi²
Median age39.0
Households~174K
Avg HH size2.70

ACS 2024 5-year estimates, county-level (Alameda County). Includes Oakland plus other Alameda municipalities in the demographic aggregates — county is the smallest official ACS geography matching where Oakland city data lives.

Housing
Units~189K
Median rent$2,357
Median home value$1.09M
Vacancy7.9%
Tenure
Renter 57%Owner 43%
Stock
SFH 47%2–4 unit 17%5+ unit 36%
Economy & people
Median HH income$129,367
Poverty rate13.3%
Unemployment6.4%
Bachelor's+49.0%
Foreign-born27.3%
Age distribution
<18 19%18–34 26%35–64 41%65+ 15%

City-level only. We deliberately do not juxtapose these with neighborhood-level crime data — see the methodology for why.

Built environment
Street miles~825
Parks (acres)~3,200
BART stations8
Walk score73 (very walkable)

Mixed-density city: walkable flatlands corridors (Telegraph, College, International) coexist with car-dependent hills neighborhoods. Crime-rate denominators differ sharply between the two.

Policing context
OPD sworn officers~700
Officers / 10K res.~16
911 calls / yr~600K
Open data lag≈ 30 days (settled)

OPD migrated to NIBRS reporting in 2021; pre-2021 records use a different taxonomy and are excluded from the analysis window. CrimeWatch metadata cites a 90-day post-month processing window, but in practice ~92% of incidents land in the feed within 30 days — the briefing uses a 30-day settle buffer. The most recent reported month may show a small undercount.

Interactive map

Every neighborhood, color-coded

CLICK A NEIGHBORHOOD →
Category
Layer
Window
RAW COUNT · 1Y
1181,1392,159
Rankings

Largest moves this month

RANKED BY ANOMALY STRENGTH
#NeighborhoodCategoryMoMYoY 12movs baseline90-day trendSignal
01MillsmontHomicide0%+25%+83%SPIKE
02Piedmont PinesOther Larceny+350%+6%+33%SPIKE
03RockridgeTheft from Vehicle-29%+67%+81%SPIKE
04Piedmont PinesAggravated AssaultSTREAK BREAK
05San AntonioRobbery-50%-56%-64%DROP
06Seminary ParkVandalism0%-22%-34%DROP
07West OaklandBurglary-42%-44%-52%DROP
08Maxwell ParkVandalism-17%-44%-58%DROP
09Brookfield VillageMotor Vehicle Theft+18%-38%-53%DROP
10GlenviewAggravated Assault-100%-38%-54%DROP
11Lockwood GardensMotor Vehicle Theft+22%-36%-50%DROP
12FruitvaleRobbery-8%-56%-63%DROP
Showing top 12 of 20 (neighborhood × category) cells with tracked signals.
Multi-year trends

The long arc — eight years of monthly counts

SELECT A CATEGORY ↓
0275380106201820192020202120222023202420252026monthly12-mo rolling mean
Latest 12mo716
YoY 12mo-13%
5-year change+214%
Window change
Peak (12mo avg)74 · Jan '24
Trough (12mo avg)60 · Mar '26
ALL CATEGORIES · 8-YEAR ARC · 12-MO ROLLING MEAN
2018 ─────────────────── 2026
When does it happen?

Hour-of-day, day-of-week, and seasonality

Distribution of bucketed incidents citywide 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
07,82515,65012am6am12pm6pm11pm

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

DAY OF WEEK · ALL CATEGORIES
018,61337,226MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
011,34322,686JanFebMarAprMayJunJulAugSepOctNovDec
Methodology

How We Calculate Oakland Crime Trends

Open about how we define spikes, what we exclude as noise, where the data comes from, and how often the model is wrong.

# anomaly rule — spike
flag = (z >= 2.5) AND (current_12mo >= 20) AND (current_6mo above sustained band)
where z = (current_12mo − μ_baseline) / σ_baseline
# exclusions (excerpt)
· simple assault (varies by reporting practice)
· drug offenses (reflect policing policy)
· admin records, weapons-possession, fraud
# 2025 backtest (citywide)
7 of 10 categories ≥ 90% coverage. see table →