Hayes Valley Crime Rate Trends — San Francisco
Hayes Valley is a walkable residential and commercial neighborhood west of City Hall, transformed since the 1989 Loma Prieta earthquake demolished the Central Freeway that once divided it. Today it is known for its boutiques, design-forward restaurants, art galleries, and the central green space of Patricia's Green amid Victorian and Edwardian architecture.
Hayes Valley had three tracked signals in June 2026 — two single-month below-trend moves and one sustained structural shift. The shape is broadly downward across property crime, with no spikes and no rare events in the mix.
Vandalism and motor vehicle theft both ran below trend this month; vandalism's trailing 12-month total stands at 156 incidents against a multi-year baseline of 284.09. Theft from vehicle is the structural story: 183 incidents over the current 12 months against 318 in the prior year, a 42.5% decline that reflects a multi-month shift rather than a single quiet period. Other larceny is the one category moving the other direction, up 6.9% year-over-year, but it did not cross a signal threshold this month.
Notable signals 2
Vandalism
The past 12 months saw 156 incidents — about 45% below the 284 average from prior years.
Motor Vehicle Theft
The past 12 months saw 90 incidents — about 51% below the 183 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 183, down 43% 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 June 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 Hayes Valley 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.”
Castro/Upper Market
146 incidents over the past 12 months — 10 below Hayes Valley's 156.
Open page →Nob Hill
169 incidents over the past 12 months — 13 above Hayes Valley's 156.
Open page →Sunset/Parkside
182 incidents over the past 12 months — 26 above Hayes Valley's 156.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Hayes Valley, 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.