Eastmont Crime Rate Trends — Oakland
Eastmont is an East Oakland residential and commercial district centered on the Eastmont Town Center on MacArthur Boulevard, between the Mills College campus and 73rd Avenue. Predominantly single-family housing along sloped streets stretching toward the foothills.
Four categories moved in Eastmont this March — three one-month below-trend signals and one sustained structural shift. The dominant pattern is downward across theft and violent crime, with no spikes and nothing running above trend.
Motor vehicle theft is the strongest signal: 209 incidents over the current 12 months against a baseline of 343.98, and down 25.4% year-over-year. Robbery and theft from vehicle both ran below trend as well, with robbery down 35.7% against the prior 12 months (36 vs. 56). Every other tracked category either moved modestly or stayed within its normal range.
Notable signals 3
Motor Vehicle Theft
The past 12 months saw 209 incidents — about 39% below the 344 average from prior years.
Robbery
The past 12 months saw 36 incidents — about 47% below the 68 average from prior years.
Theft from Vehicle
The past 12 months saw 52 incidents — about 47% below the 99 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.
- Motor Vehicle Theft has reset to a lower baseline.
The trailing 12-month count is 209, down 25% from 280 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 March 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 Eastmont 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.”
Eastlake
208 incidents over the past 12 months — 1 below Eastmont's 209.
Open page →Brookfield Village
211 incidents over the past 12 months — 2 above Eastmont's 209.
Open page →San Antonio
203 incidents over the past 12 months — 6 below Eastmont's 209.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Eastmont, 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 SFPD's open dataset, 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.