Glen Park Crime Rate Trends — San Francisco
Glen Park is a small, residential village clustered around the Glen Park BART station and its short Diamond/Chenery commercial strip. It feels distinctly small-town within the city, with the rugged 70-acre Glen Canyon Park — a rare stretch of unmanicured native landscape in San Francisco — at its eastern edge.
Three signals surfaced in Glen Park in March 2026 — two one-month below-trend readings and one sustained structural shift. The shape is narrowly focused: theft from vehicle is doing the heavy lifting, appearing as both a single-month drop and a multi-month structural decline, while vandalism rounds out the below-trend picture. Nothing else crossed the anomaly threshold.
Theft from vehicle is the defining trend: the current 12-month total is 37 incidents against a prior-year total of 81, a 54.3% decrease year over year. The sustained-shift signal confirms this isn't a single quiet month — the volume has structurally reset lower. Vandalism follows a similar direction, down 16.2% to 31 incidents from 37. All other tracked categories — robbery, burglary, motor vehicle theft, aggravated assault, other larceny — remained within their normal ranges this month.
Notable signals 2
Theft from Vehicle
The past 12 months saw 37 incidents — about 76% below the 152 average from prior years.
Vandalism
The past 12 months saw 31 incidents — about 41% below the 52 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 37, down 54% from 81 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 Glen Park compares
Peer neighborhoods picked by closest 12-month theft from vehicle 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 theft from vehicle levels.”
Twin Peaks
37 incidents over the past 12 months — 0 below Glen Park's 37.
Open page →Visitacion Valley
47 incidents over the past 12 months — 10 above Glen Park's 37.
Open page →Presidio Heights
55 incidents over the past 12 months — 18 above Glen Park's 37.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Glen Park, 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.