Green Meadows Crime Rate Trends — Los Angeles
Green Meadows is a South LA residential neighborhood around 92nd Street and Avalon Boulevard, between Florence and Watts. Predominantly single-family bungalows on a tight grid, anchored by Green Meadows Recreation Center and the 92nd Street Elementary corridor.
Six categories moved in Green Meadows this April — four ran below trend in the current window, two registered as sustained structural shifts. The overall shape is broadly downward across property and violent crime, with no spikes or rare-event signals in the mix.
Motor vehicle theft leads the signals: the trailing 12-month total is 209 against a baseline mean of 431.23 — down 49.6% year over year. Aggravated assault and theft from vehicle also ran below trend, with aggravated assault off 17.4% (246 incidents vs. 298) and theft from vehicle down 23.0% (137 vs. 178). The two sustained-shift signals point to structural change, not just a quiet month.
Notable signals 4
Motor Vehicle Theft
The past 12 months saw 209 incidents — about 52% below the 431 average from prior years.
Aggravated Assault
The past 12 months saw 246 incidents — about 28% below the 342 average from prior years.
Theft from Vehicle
The past 12 months saw 137 incidents — about 39% below the 225 average from prior years.
Burglary
The past 12 months saw 46 incidents — about 43% below the 80 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 has reset to a lower baseline.
The trailing 12-month count is 209, down 50% from 415 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 46, down 47% from 86 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 April 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 Green Meadows compares
Peer neighborhoods picked by closest 12-month motor vehicle theft 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 motor vehicle theft levels.”
Hyde Park
217 incidents over the past 12 months — 8 above Green Meadows's 209.
Open page →Central-Alameda
222 incidents over the past 12 months — 13 above Green Meadows's 209.
Open page →Vermont Knolls
232 incidents over the past 12 months — 23 above Green Meadows's 209.
Open page →Do crime spikes here spill over to adjacent neighborhoods?
When Green Meadows has spiked other larceny historically (11 events on record), an adjacent neighborhood spiked the same category within 3 months 100% of the time. The strongest-travelling categories sit at the top of the table.
| Category | Spike events | Same-category spillover |
|---|---|---|
| Other larceny | 11 | 100% |
| Robbery | 11 | 27.3% |
Each row shows Green Meadows's historical spike events for that category, and how often any of its 3 adjacent neighborhoods spiked the same category within the next 3 months. A high same-category rate suggests a shock that travels (e.g. theft crews moving across Los Angeles); a low rate means spikes here tend to be local to the neighborhood. Categories with fewer than 5 historical spike events are listed but their rates are suppressed.
Recurring local terms (last 12 months)
Top terms in incident descriptions for Green Meadows, 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
Counts from March 2024 onwardrun roughly 10 to 20 percent below LAPD's command-staff totals citywide. LAPD's legacy crime feed froze after a late-2024 cyber incident, and the replacement NIBRS feed has been shipping fewer rows than LAPD's own statistics show. The shortfall is most visible in homicide and in dense south-LA neighborhoods, because the new feed lacks coordinates and resolves location through reporting districts. Trend direction is still meaningful; absolute levels are not directly comparable to LAPD's headline figures.
Data → Anomalies → Forecast → Page
Incident data is pulled from LAPD's open feed on the LA City Open Data portal — the NIBRS-coded feed from 2024-03 onward with UCR backfill to 2020. 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.