Clifton Crime Rate Trends — Cincinnati
Clifton is a hillside residential neighborhood north of the University of Cincinnati, anchored by the Ludlow Avenue commercial strip in the Gaslight District and Clifton Avenue running north-south. Mostly historic single-family homes, with Burnet Woods park and Mt. Storm park on the bluff edges.
September 2026 was a quiet month in Clifton. No tracked category produced a notable signal, and the month's data reflects the broader structural story the trailing 12 months have been telling: volume is down across most categories, with theft from vehicle the lone exception.
Robbery is the sharpest mover in the 12-month window, 5 incidents against 18 in the prior year, a 72.2% reduction. Burglary fell 41.2% over the same period, 30 incidents vs. 51, and aggravated assault is down 29.4%, from 17 to 12. Theft from vehicle ran in the other direction, 75 incidents against 63, a 19.0% increase, the only category above its prior-year pace. Everything else was within a downward trend that now spans multiple categories across the neighborhood.
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 September 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.
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
How Clifton 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.”
Evanston
91 incidents over the past 12 months — 1 below Clifton's 92.
Open page →College Hill
90 incidents over the past 12 months — 2 below Clifton's 92.
Open page →Mt. Airy
99 incidents over the past 12 months — 7 above Clifton's 92.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Clifton, 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 Cincinnati Open Data — STARS Category Offenses post-2024-06-03 plus PDI Crime Incidents back to 2020 — mapped to 8 UCR-aligned categories (vandalism and arson aren't recoverable across the STARS migration boundary). Aggregated to Statistical Neighborhood Approximation × 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.