Oakmore Highlands Crime Rate Trends — Oakland
Oakmore Highlands is a foothill neighborhood between Park Boulevard and the Mountain Boulevard ridge, organized around the Sausal Creek watershed and Park Boulevard. Single-family housing on sloped, wooded streets, with the Oakmore Pool and Sausal Creek Trail as community anchors.
Oakmore Highlands recorded one tracked signal in July 2026, a sustained multi-month structural shift in motor vehicle theft. The rest of the tracked categories were within normal range. This is not a noisy month with scattered one-off moves; the data shows a single durable pattern holding across an extended window.
Motor vehicle theft is down 42.9% against the prior 12 months, 40 incidents in the current year versus 70 the year before, and the sustained-shift classification means that gap has persisted long enough to reflect a structural change rather than a single quiet month. Burglary and theft from vehicle also show large year-over-year declines, 48.7% and 58.1% respectively, though neither crossed the threshold for a tracked signal this period. Other larceny is the one category moving in the opposite direction, up 27.3% over the same span, 70 incidents against 55, a counter-trend worth watching even without a formal signal this month.
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.
- Motor Vehicle Theft has reset to a lower baseline.
The trailing 12-month count is 40, down 43% from 70 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
Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.
Vandalism
Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.
How Oakmore Highlands 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.”
Clinton
39 incidents over the past 12 months — 1 below Oakmore Highlands's 40.
Open page →Jingletown
41 incidents over the past 12 months — 1 above Oakmore Highlands's 40.
Open page →Upper Rockridge
47 incidents over the past 12 months — 7 above Oakmore Highlands's 40.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Oakmore Highlands, 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.