Oakland Crime Rate Trends — Chicago
Oakland is a small South Side lakefront neighborhood between Bronzeville and Kenwood, organized around the Metra Electric line. Predominantly mid-century apartment buildings; bordered by Lake Michigan to the east and Mandrake Park along the lakefront.
August 2026 produced no notable signals in Oakland. Across all six tracked categories, none crossed the anomaly threshold for the month, making this a genuinely quiet briefing with no spikes, drops, sustained shifts, or rare events to report.
The 12-month picture offers some context. Burglary is the sharpest mover over the trailing year, 15 incidents against 10 in the prior 12 months, a 50.0% rise, though the counts remain small. Robbery moved the other direction, down 23.5% year-over-year (13 vs. 17). Other larceny and motor vehicle theft, the two highest-volume categories, sit at 157 and 127 incidents respectively for the trailing 12 months, both within a few percentage points of the prior year. Nothing in this month's data broke from those trends.
Notable signals 0
Nothing notable surfaced this month — every category sits within normal range against its baseline.
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.
No sustained shifts surfaced this month.
What next month likely looks like
Forecasts trained through August 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
Below the volume threshold for a reliable forecast — too few incidents in recent months to project from.
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.
Vandalism
How Oakland compares
Peer neighborhoods picked by closest 12-month other larceny 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 other larceny levels.”
Montclare
163 incidents over the past 12 months — 6 above Oakland's 157.
Open page →West Elsdon
140 incidents over the past 12 months — 17 below Oakland's 157.
Open page →Hegewisch
136 incidents over the past 12 months — 21 below Oakland's 157.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Oakland, 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 CPD's open dataset on the City of Chicago Open Data portal — IUCR-coded and mapped to 9 UCR-aligned categories (theft from vehicle isn't reliably separable in the public feed and rolls into other larceny). Aggregated to community area × 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.