Chesterfield Square Crime Rate Trends — Los Angeles
Chesterfield Square is a small South LA residential pocket organized around Western Avenue and Slauson, between Hyde Park and Vermont Square. Predominantly single-family bungalows on a quiet grid, with the Chesterfield Square shopping center on Western as the local commercial anchor.
Four categories moved in Chesterfield Square this March — three single-month spikes and one sustained structural shift. The shape of the month is upward pressure on vehicle-related crime and vandalism, sitting against a backdrop of multi-year declines in violent categories across the neighborhood.
Theft from Vehicle, Motor Vehicle Theft, and Vandalism all registered above-trend signals this month. Theft from Vehicle is the sharpest: 86 incidents in the trailing 12 months against a prior-year total of 68, a 26.5% increase year-over-year. Motor Vehicle Theft is more pronounced at the annual level — 139 incidents vs. 92 prior, up 51.1% — making the spike this month part of a steeper climb. Violent categories moved the other direction over the same window: Aggravated Assault is down 25.9% year-over-year (109 vs. 147) and Sexual Assault down 55.0% (9 vs. 20), both well outside the range of the vehicle-crime trend.
Notable signals 3
Theft from Vehicle
The past 12 months saw 86 incidents — about 53% above the 56 average from prior years.
Motor Vehicle Theft
The past 12 months saw 139 incidents — about 36% above the 102 average from prior years.
Vandalism
The past 12 months saw 105 incidents — about 72% above the 61 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.
- Motor Vehicle Theft is climbing.
The trailing 12-month count is 139, up 51% from 92 the year before. If the trend holds another quarter, it will pull the multi-year baseline up.
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 Chesterfield Square 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.”
Lake Balboa
85 incidents over the past 12 months — 1 below Chesterfield Square's 86.
Open page →Arlington Heights
82 incidents over the past 12 months — 4 below Chesterfield Square's 86.
Open page →Brentwood
90 incidents over the past 12 months — 4 above Chesterfield Square's 86.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Chesterfield Square, 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.