Shadow Hills Crime Rate Trends — Los Angeles
Shadow Hills is a northeastern San Fernando Valley neighborhood between Sunland and Sun Valley, organized around the Hansen Dam recreation area and the equestrian streets that run through the neighborhood.
Three signals moved in Shadow Hills this March — two one-month below-trend readings and one sustained structural shift. The dominant shape is downward across vehicle-related property crime, with both motor vehicle theft and theft from vehicle running below their baselines and the latter showing a multi-month structural decline, not just a quiet week.
Motor vehicle theft is the sharpest single-month signal: 36 incidents over the current 12 months against a baseline of 66, a gap that reflects a durable change in volume, not random variation. Theft from vehicle compounds that picture — down 68.7% year-over-year, 21 incidents against 67 in the prior 12 months — and the sustained-shift signal confirms the drop predates this month. Every other tracked category in Shadow Hills, including robbery, burglary, and vandalism, finished within a quieter range; the story here is concentrated in the vehicle crime columns.
Notable signals 2
Motor Vehicle Theft
The past 12 months saw 36 incidents — about 45% below the 66 average from prior years.
Theft from Vehicle
The past 12 months saw 21 incidents — about 77% below the 90 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 21, down 69% from 67 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 Shadow Hills 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.”
Cypress Park
36 incidents over the past 12 months — 0 below Shadow Hills's 36.
Open page →Mission Hills
37 incidents over the past 12 months — 1 above Shadow Hills's 36.
Open page →Sunland
35 incidents over the past 12 months — 1 below Shadow Hills's 36.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Shadow Hills, 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.