Valley Village Crime Rate Trends — Los Angeles
Valley Village is a southeastern San Fernando Valley neighborhood between North Hollywood and Studio City, organized around Magnolia Boulevard. Predominantly mid-century single-family homes and small apartment buildings.
Three categories moved in Valley Village this March — two ran below trend and one registered an above-trend signal. The structural picture is mixed: most property crime categories are down on a 12-month basis, but vandalism is pulling against that direction.
Burglary and other larceny both came in below trend this month; over the trailing 12 months, burglary is down 25.3% (68 incidents vs. 91 in the prior year) and other larceny is down 17.3% (81 vs. 98). Vandalism moved the other way — the spike signal sits against a 12-month total of 131 incidents, up from 129 in the prior year, with the current volume running above its multi-year baseline. Everything else in the tracked categories — robbery, aggravated assault, theft from vehicle, motor vehicle theft, sexual assault — fell outside the signal threshold this month.
Notable signals 3
Vandalism
The past 12 months saw 131 incidents — about 54% above the 85 average from prior years.
Burglary
The past 12 months saw 68 incidents — about 34% below the 103 average from prior years.
Other Larceny
The past 12 months saw 81 incidents — about 38% below the 130 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.
No sustained shifts surfaced this month.
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 Valley Village 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.”
Hollywood Hills
131 incidents over the past 12 months — 0 below Valley Village's 131.
Open page →Highland Park
130 incidents over the past 12 months — 1 below Valley Village's 131.
Open page →Sylmar
130 incidents over the past 12 months — 1 below Valley Village's 131.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Valley Village, 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.