Sawtelle Crime Rate Trends — Los Angeles
Sawtelle is a Westside neighborhood organized around Sawtelle Boulevard south of Wilshire. A dense restaurant-and-retail strip in a predominantly small-apartment-and-single-family neighborhood; bordered by the VA medical campus to the north.
Three categories moved in Sawtelle in March 2026 — one one-month below-trend signal and two structural sustained shifts. The shape is mixed: property theft is broadly lower, but burglary has been rising at the structural level for over a year, pulling in the opposite direction from the larceny categories.
Theft from vehicle is the strongest single-month signal, with 219 incidents over the trailing 12 months against a multi-year baseline of 369.92 — a substantial gap. Burglary tells a different story: 86 incidents in the current 12 months vs. 53 in the prior 12, up 62.3%, a sustained shift rather than a one-month anomaly. Other larceny moved the other way structurally, dropping from 813 to 446, down 45.1% year over year. Everything else — robbery, aggravated assault, vandalism, motor vehicle theft, arson — came in within normal range.
Notable signals 1
Theft from Vehicle
The past 12 months saw 219 incidents — about 41% below the 370 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 446, down 45% from 813 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
- Burglary is climbing.
The trailing 12-month count is 86, up 62% from 53 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 Sawtelle 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.”
Echo Park
219 incidents over the past 12 months — 0 below Sawtelle's 219.
Open page →Pico-Union
218 incidents over the past 12 months — 1 below Sawtelle's 219.
Open page →Winnetka
220 incidents over the past 12 months — 1 above Sawtelle's 219.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Sawtelle, 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.