CINCINNATI · 8.0K residents

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.

OTHER LARCENY · 24-MO COUNT06 2026 · 8
0122312-mo avg: 8.6
CLIFTONCITYWIDE TREND (RESCALED)+2% 12MO YOY
+100%MoM
-6%12mo YoY
103last 12mo
8this month
01 · TL;DR

June 2026 was a quiet month in Clifton. No tracked category crossed an anomaly threshold — zero signals of any type across the full crime mix. The structural picture is still worth reading: the 12-month data shows broad declines in most property and violent crime categories, with one exception.

Robbery is down 66.7% against the prior 12 months (6 incidents vs. 18), and burglary is down 38.9% (33 vs. 54). Motor vehicle theft fell 34.7% over the same window. The outlier is theft from vehicle, up 20.3% year-over-year — 77 incidents against 64 in the prior 12 months — the one category running above its recent baseline while everything else held flat or declined.

No signals this month
02 · Notable signals

Notable signals 0

Nothing notable surfaced this month — every category sits within normal range against its baseline.

03 · By category

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.

Homicidebelow threshold
2024-072026-06
Robberybelow threshold
2024-072026-06
Aggravated Assault-7%
2024-072026-06
Sexual Assaultbelow threshold
2024-072026-06
Burglary-39%
2024-072026-06
Theft from Vehicle+20%
2024-072026-06
Other Larceny-6%
2024-072026-06
Motor Vehicle Theft-35%
2024-072026-06
05 · Forecast

What next month likely looks like

Forecasts trained through June 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

NO FORECAST

Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.

Burglary

JULY 2026
Most likely 5 next month — likely between 1 and 8.
+65% vs 12-month average (≈2.8)

Homicide

NO FORECAST

Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.

Motor Vehicle Theft

JULY 2026
Most likely 10 next month — likely between 4 and 16.
+153% vs 12-month average (≈3.9)

Other Larceny

JULY 2026
Most likely 13 next month — likely between 8 and 18.
+50% vs 12-month average (≈8.6)

Robbery

NO FORECAST

Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.

Sexual Assault

NO FORECAST

Too low-volume per neighborhood for a reliable point forecast — see the rare-event and streak-break signals above instead.

Theft from Vehicle

JULY 2026
Most likely 9 next month — likely between 4 and 14.
+39% vs 12-month average (≈6.4)
06 · Context & comps

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.”

07 · Patterns

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.

partpersonalrapestrangulation
When does it happen?

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.

HOUR OF DAY · ALL CATEGORIES
012925912am6am12pm6pm11pm

Hour 0 is mildly inflated by reports without a known time defaulting to midnight — see methodology.

DAY OF WEEK · ALL CATEGORIES
0178356MonTueWedThuFriSatSun
MONTH OF YEAR · ALL CATEGORIES
0124249JanFebMarAprMayJunJulAugSepOctNovDec
08 · Methodology

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.