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.
Glen Park's June 2026 briefing is narrow in scope but consistent in direction: two signals, both on theft from vehicle, one a single-month below-trend reading and one a sustained multi-month structural shift downward. No other category crossed the anomaly threshold.
Theft from vehicle is the defining story across the trailing 12 months — 24 incidents against 83 in the prior year, a 71.1% decline. That sustained-shift signal reflects a structural change, not a one-month anomaly. The rest of the category mix reinforces the broader direction: robbery down 63.6% (4 vs. 11), aggravated assault down 55.6% (4 vs. 9), burglary down 26.5% (36 vs. 49), and motor vehicle theft down 38.3% (29 vs. 47). Other larceny and vandalism were essentially flat.
Notable signals 1
Theft from Vehicle
The past 12 months saw 24 incidents — about 84% below the 150 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 24, down 71% from 83 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 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
29 incidents over the past 12 months — 5 above Glen Park's 24.
Open page →Lincoln Park
13 incidents over the past 12 months — 11 below Glen Park's 24.
Open page →Presidio
10 incidents over the past 12 months — 14 below Glen Park's 24.
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 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.