Inner Richmond Crime Rate Trends — San Francisco
The Inner Richmond is a residential neighborhood north of Golden Gate Park, anchored by the Geary Boulevard and Clement Street commercial corridors. Long known for its dim sum restaurants, neighborhood bakeries, and a steady mix of long-established small businesses, it has a fog-belt climate and a lived-in pace.
Four tracked signals shaped Inner Richmond's April 2026 briefing — two one-month below-trend reads and two sustained multi-month structural shifts, with the overall direction running downward across property crime categories.
Vandalism and theft from vehicle both ran below trend this month; burglary is the more structural story, down 48.7% over the trailing 12 months against the prior 12 (58 incidents vs. 113). Robbery shows a similar long-run contraction at -69.2% year-over-year. Aggravated assault and other larceny moved the other direction — up 18.2% and 10.8% respectively — but neither crossed the anomaly threshold this period.
Notable signals 2
Vandalism
The past 12 months saw 75 incidents — about 40% below the 126 average from prior years.
Theft from Vehicle
The past 12 months saw 56 incidents — about 81% below the 292 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 58, down 49% from 113 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
- Theft from Vehicle has reset to a lower baseline.
The trailing 12-month count is 56, down 36% from 87 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 April 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 Inner Richmond compares
Peer neighborhoods picked by closest 12-month vandalism 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 vandalism levels.”
Portola
77 incidents over the past 12 months — 2 above Inner Richmond's 75.
Open page →Visitacion Valley
78 incidents over the past 12 months — 3 above Inner Richmond's 75.
Open page →Inner Sunset
70 incidents over the past 12 months — 5 below Inner Richmond's 75.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Inner Richmond, 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 on DataSF, 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.