Melrose Crime Rate Trends — Oakland
Melrose is an East Oakland residential neighborhood centered on the High Street and MacArthur Boulevard intersection, bounded by I-580 and the Mills College campus. Mostly single-family housing with a small commercial strip on High Street near Foothill Boulevard.
Two categories moved in Melrose this March — one single-month below-trend signal and one structural, multi-month shift. The overall picture is downward, particularly across property crime, with motor vehicle theft and burglary accounting for both signals.
Motor vehicle theft registered the month's most prominent signal: the current 12-month total of 244 incidents sits well below the baseline mean of 440.7. Burglary is a sustained shift rather than a one-month dip — 73 incidents over the trailing 12 months against 114 the prior year, a 36.0% decrease that reflects a multi-year structural change in that category. Everything else in Melrose — robbery, aggravated assault, other larceny, vandalism — ran within normal range this month.
Notable signals 1
Motor Vehicle Theft
The past 12 months saw 244 incidents — about 45% below the 441 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.
- Burglary has reset to a lower baseline.
The trailing 12-month count is 73, down 36% from 114 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 Melrose 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.”
Jack London Square
237 incidents over the past 12 months — 7 below Melrose's 244.
Open page →Dimond District
230 incidents over the past 12 months — 14 below Melrose's 244.
Open page →Maxwell Park
259 incidents over the past 12 months — 15 above Melrose's 244.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Melrose, 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.