CUF Crime Rate Trends — Cincinnati
CUF stands for Clifton Heights, University Heights, and Fairview, the dense neighborhood immediately south and west of the University of Cincinnati's main campus. Mixed student housing, hillside residential streets, and the McMillan Street and Calhoun Street commercial strips that serve the campus.
June 2026 produced two signals in CUF — one spike and one sustained structural shift — against an otherwise quiet month. The spike is in aggravated assault; the sustained shift is in other larceny, running well below its multi-year baseline. Two categories moved; the rest held within normal range.
Other larceny is down 37.5% over the trailing 12 months — 205 incidents against 328 in the prior year — a structural drop large enough to represent a meaningful change in baseline, not just a quiet stretch. Aggravated assault sits at 24 incidents over the current 12 months, flat against the prior year's 26 but registering a one-month spike this period. Burglary also declined over the 12-month window, off 14.9% to 103 incidents, though it did not cross a signal threshold this month.
Notable signals 1
Aggravated Assault
The past 12 months saw 24 incidents — about 80% above the 13 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.
- Other Larceny has reset to a lower baseline.
The trailing 12-month count is 205, down 38% from 328 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 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
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 CUF compares
Peer neighborhoods picked by closest 12-month aggravated assault 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 aggravated assault levels.”
Millvale
25 incidents over the past 12 months — 1 above CUF's 24.
Open page →Northside
23 incidents over the past 12 months — 1 below CUF's 24.
Open page →Bond Hill
22 incidents over the past 12 months — 2 below CUF's 24.
Open page →Do crime spikes here spill over to adjacent neighborhoods?
CUFdoesn't have enough spike history in any single category for a stable spillover rate yet (we want at least 5 events). The table below lists what we have.
| Category | Spike events | Same-category spillover |
|---|---|---|
| Aggravated assault | 1 | — too few |
Each row shows CUF's historical spike events for that category, and how often any of its 7 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 Cincinnati); 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 CUF, 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.