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.
Four categories moved in Grand Lake this May — three one-month below-trend signals and one sustained structural shift. The overall shape is broadly downward across property crime, with theft from vehicle, other larceny, and vandalism all running below trend in the same month.
Other larceny is the strongest single signal: the current 12-month total is 162 incidents against a baseline of 214.21, and down 18.2% against the prior 12-month period of 198. Theft from vehicle shows the sharpest year-over-year move in the category data — 115 incidents in the current 12 months versus 181 in the prior year, a 36.5% reduction. Vandalism also ran below trend, with 65 incidents this year against 84 the prior period, down 22.6%. Everything else in the tracked categories was within range.
Notable signals 3
Other Larceny
The past 12 months saw 162 incidents — about 24% below the 214 average from prior years.
Vandalism
The past 12 months saw 65 incidents — about 68% below the 206 average from prior years.
Theft from Vehicle
The past 12 months saw 115 incidents — about 65% below the 330 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 115, down 37% from 181 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 May 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.”
Westlake
160 incidents over the past 12 months — 2 below Grand Lake's 162.
Open page →San Antonio
158 incidents over the past 12 months — 4 below Grand Lake's 162.
Open page →Uptown
156 incidents over the past 12 months — 6 below Grand Lake's 162.
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.