Grand Lake Crime Rate Trends — Oakland
Grand Lake is a Lake Merritt-adjacent neighborhood organized around the Grand Lake Theatre, the Grand Avenue commercial strip, and Lakeshore Avenue. A mix of pre-war apartment buildings and Victorian houses, with weekend farmers markets at Splash Pad Park.
Three signals defined Grand Lake's July 2026 briefing: two one-month below-trend readings and one sustained structural shift. The structural story is theft from vehicle, which has moved well below its multi-year pace over the trailing 12 months, not just a quiet month but a durable change in the category's level. Other larceny registered the stronger single-month signal, while the rest of the tracked categories stayed within normal range.
Theft from vehicle is down 42.2% against the prior 12 months, 96 incidents versus 166, and the sustained-shift signal confirms that gap has persisted across multiple months, not a one-time dip. Other larceny sits at 149 incidents over the current 12 months against 195 in the year before, a 23.6% reduction. Vandalism and robbery also ran lower year-over-year, down 17.1% and 16.0% respectively, though neither crossed the signal threshold this month.
Notable signals 2
Other Larceny
The past 12 months saw 149 incidents — about 30% below the 214 average from prior years.
Theft from Vehicle
The past 12 months saw 96 incidents — about 70% below the 322 average from prior years.
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.
What's been quietly true for a year
Spikes get attention. Sustained shifts shape policy. These are multi-quarter patterns where the past 12-month total differs meaningfully from the year before — they often precede the baseline resetting.
- Theft from Vehicle has reset to a lower baseline.
The trailing 12-month count is 96, down 42% from 166 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
What next month likely looks like
Forecasts trained through July 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
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Arson
Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.
Burglary
Homicide
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Motor Vehicle Theft
Other Larceny
Robbery
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Sexual Assault
Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.
Theft from Vehicle
Vandalism
How Grand Lake 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.”
Longfellow
151 incidents over the past 12 months — 2 above Grand Lake's 149.
Open page →Melrose
151 incidents over the past 12 months — 2 above Grand Lake's 149.
Open page →San Antonio
154 incidents over the past 12 months — 5 above Grand Lake's 149.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Grand Lake, excluding generic crime taxonomy. Useful as texture — what kinds of specifics show up here that don't show up elsewhere.
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.
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.