DROP · MOTOR VEHICLE THEFTMARCH 2026 BRIEFINGOAKLAND · 46.9K residents

Elmhurst Crime Rate Trends — Oakland

Elmhurst is a sprawling East Oakland neighborhood between 73rd and 98th Avenues, bordered by I-580 to the east. A mix of residential blocks, commercial corridors along International Boulevard, and the historic Elmhurst Library on Bancroft Avenue.

MOTOR VEHICLE THEFT · 24-MO COUNT03 2026 · 38
05110212-mo avg: 47.5
ELMHURSTCITYWIDE TREND (RESCALED)-25% 12MO YOY
-3%MoM
-21%12mo YoY
570last 12mo
38this month
01 · TL;DR

Seven categories moved in Elmhurst in March 2026 — four ran below trend in the current month, three registered as sustained structural shifts over the trailing 12 months. The overall shape is broadly downward, with no spikes or rare-event signals anywhere in the mix.

Motor vehicle theft is the most prominent signal: 570 incidents over the current 12 months against a baseline of 861.7, and down 21.2% against the prior-year period of 723. Robbery and vandalism also ran below trend this month — robbery is down 29.6% year-over-year (152 vs. 216) and vandalism is down 21.8% (233 vs. 298). All other tracked categories were within their expected ranges, with sexual assault and arson the only two categories running above their prior-year levels.

4 drops3 sustained shifts
02 · Notable signals

Notable signals 4

DROP · MOTOR VEHICLE THEFTZ = 4.00

Motor Vehicle Theft

The past 12 months saw 570 incidents — about 34% below the 862 average from prior years.

DROP · ROBBERYZ = 3.88

Robbery

The past 12 months saw 152 incidents — about 35% below the 232 average from prior years.

DROP · VANDALISMZ = 3.79

Vandalism

The past 12 months saw 233 incidents — about 31% below the 336 average from prior years.

DROP · AGGRAVATED ASSAULTZ = 2.86

Aggravated Assault

The past 12 months saw 301 incidents — about 47% below the 572 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-9%
2024-042026-03
Robbery-30%
2024-042026-03
Aggravated Assault-30%
2024-042026-03
Sexual Assault+21%
2024-042026-03
Burglary-27%
2024-042026-03
Theft from Vehicle-22%
2024-042026-03
Other Larceny-18%
2024-042026-03
Motor Vehicle Theft-21%
2024-042026-03
Vandalism-22%
2024-042026-03
Arson+25%
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 13 next month — likely between 4 and 22.
+28% vs 12-month average (≈10.3)

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 47 next month — likely between 24 and 72.
0% vs 12-month average (≈47.5)

Other Larceny

APRIL 2026
Most likely 50 next month — likely between 36 and 65.
+8% vs 12-month average (≈46.3)

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 10 next month — likely between 2 and 20.
+28% vs 12-month average (≈8.2)

Vandalism

APRIL 2026
Most likely 21 next month — likely between 11 and 30.
+9% vs 12-month average (≈19.4)
06 · Context & comps

How Elmhurst 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 Elmhurst, excluding generic crime taxonomy. Useful as texture — what kinds of specifics show up here that don't show up elsewhere.

firearmspousemannernegligentweaponforcedatedischargewillfulgrandcourtterrorizedangerousdeathpossessinjuryinflictunexplainedintentorderthreatedthreatscohabitantcorporalcarry
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
07101,42012am6am12pm6pm11pm

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

DAY OF WEEK · ALL CATEGORIES
01,3062,611MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
08441,687JanFebMarAprMayJunJulAugSepOctNovDec
08 · Methodology

How we built this page

Data → Anomalies → Forecast → Page

Incident data is pulled from SFPD's open dataset, 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.