Glenview Crime Rate Trends — Oakland
Glenview is a residential foothill neighborhood between MacArthur Boulevard and the I-580/Park Boulevard split. Single-family bungalows on sloped, tree-lined streets, with a small commercial strip on Park Boulevard near Excelsior Avenue.
Three signals surfaced in Glenview this August: one single-month below-trend move and two sustained structural shifts. All three point in the same direction, a broad and durable decline in property crime, not a one-month dip.
Theft from vehicle is the clearest case. The trailing 12-month total stands at 54 incidents, down 59.7% against the prior year's 134, and that decline has held long enough to register as a sustained shift, not just noise. Other larceny shows the same structure: 232 incidents over the past 12 months against 318 the year before, a 27.0% reduction that the data treats as a multi-year move. Outside these two categories, no other tracked category crossed an anomaly threshold this month.
Notable signals 1
Theft from Vehicle
The past 12 months saw 54 incidents — about 77% below the 231 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 54, down 60% from 134 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
- Other Larceny has reset to a lower baseline.
The trailing 12-month count is 232, down 27% from 318 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
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 Glenview 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.”
Brookfield Village
54 incidents over the past 12 months — 0 below Glenview's 54.
Open page →Eastlake
53 incidents over the past 12 months — 1 below Glenview's 54.
Open page →Eastmont
57 incidents over the past 12 months — 3 above Glenview's 54.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Glenview, 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.