Arlington Heights Crime Rate Trends — Los Angeles
Arlington Heights is a South LA neighborhood between West Adams and Pico-Union, organized around Western Avenue and Washington Boulevard. Predominantly Craftsman bungalows and small apartment buildings.
Four categories moved in Arlington Heights this March — two single-month below-trend signals and two sustained structural shifts. The overall shape is broadly downward across property crime, with no spikes and no rare-event signals anywhere in the mix.
Burglary and motor vehicle theft both ran below trend this month; burglary's current 12-month total of 32 incidents sits well below its multi-year baseline of 77.62. The sustained-shift signals tell a longer story: theft from vehicle is down 40.6% against the prior 12 months (82 incidents vs. 138), and other larceny is down 38.4% (98 vs. 159) — structural moves that predate this month. Robbery is the one category moving the other direction, up 6.8% year-over-year, though at 47 incidents it remains a small slice of the neighborhood's overall volume.
Notable signals 2
Burglary
The past 12 months saw 32 incidents — about 59% below the 78 average from prior years.
Motor Vehicle Theft
The past 12 months saw 83 incidents — about 44% below the 147 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.
- Other Larceny has reset to a lower baseline.
The trailing 12-month count is 98, down 38% from 159 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
- Theft from Vehicle has reset to a lower baseline.
The trailing 12-month count is 82, down 41% from 138 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 Arlington Heights compares
Peer neighborhoods picked by closest 12-month burglary 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 burglary levels.”
Shadow Hills
33 incidents over the past 12 months — 1 above Arlington Heights's 32.
Open page →Vermont Vista
31 incidents over the past 12 months — 1 below Arlington Heights's 32.
Open page →Glassell Park
34 incidents over the past 12 months — 2 above Arlington Heights's 32.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Arlington Heights, 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.