Downtown Crime Rate Trends — Oakland
Downtown is Oakland's central business district, anchored by City Hall, the 12th and 19th Street BART stations, and the historic Oakland City Center. Mixed-use blocks of office towers, civic buildings, and converted warehouses, bordered by Lake Merritt to the east.
August 2026 produced a single structural signal in Downtown Oakland: a sustained downward shift in theft from vehicle, the only category that crossed the anomaly threshold this month. Every other tracked category stayed within its normal range, making this one of the quietest briefings in recent months.
Theft from vehicle is down 51.4% against the prior 12 months, 72 incidents in the current period against 148 in the year before. That is not a one-month dip; the sustained-shift classification means the gap has held across multiple months, pointing to a structural change rather than noise. Robbery and other larceny both moved modestly upward over the same 12-month window, 35.3% and 11.8% respectively, but neither crossed the threshold for a notable signal this period.
Notable signals 0
Nothing notable surfaced this month — every category sits within normal range against its baseline.
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 72, down 51% from 148 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 August 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
Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.
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 Downtown compares
Peer neighborhoods picked by closest 12-month theft from vehicle 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 theft from vehicle levels.”
Elmhurst
77 incidents over the past 12 months — 5 above Downtown's 72.
Open page →Fruitvale
64 incidents over the past 12 months — 8 below Downtown's 72.
Open page →Laurel
59 incidents over the past 12 months — 13 below Downtown's 72.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Downtown, 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.