Florence Crime Rate Trends — Los Angeles
Florence is a South LA neighborhood organized around Florence Avenue and Central Avenue. Predominantly small single-family homes; bordered by Watts to the south and South Park to the north.
Four categories moved in Florence this March — two single-month below-trend signals and two sustained structural shifts. The dominant shape is downward across both property and violent crime, with nothing running above trend anywhere in the neighborhood.
Burglary leads the signals: 52 incidents over the trailing 12 months against a multi-year baseline of 125.52, and down 45.8% against the prior 12 months (96). Robbery also ran below trend this month, sitting at 174 over the trailing year versus 191 the year before, a 8.9% decline. Sexual assault's sustained-shift signal reflects a structural move — 32 incidents in the current 12 months compared to 70 in the prior period, a 54.3% drop — a pattern that runs deeper than a single quiet month.
Notable signals 2
Burglary
The past 12 months saw 52 incidents — about 59% below the 126 average from prior years.
Robbery
The past 12 months saw 174 incidents — about 35% below the 266 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.
- Sexual Assault has reset to a lower baseline.
The trailing 12-month count is 32, down 54% from 70 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
- Burglary has reset to a lower baseline.
The trailing 12-month count is 52, down 46% from 96 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 Florence 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.”
Recurring local terms (last 12 months)
Top terms in incident descriptions for Florence, 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.