Cheesman Park Crime Rate Trends — Denver
Cheesman Park is the dense residential neighborhood surrounding the eponymous park, just east of Capitol Hill. Pre-war high-rise apartment buildings line the park's edges; the side streets are a mix of Victorians, bungalows, and four-story walk-ups.
Three signals surfaced in Cheesman Park this September, one single-month drop and two sustained structural shifts. The shape is broadly downward across property crime: motor vehicle theft is running well below its multi-year pace, and other larceny has been on a structural downward trend for long enough that September's numbers reflect a changed baseline, not a quiet month.
Motor vehicle theft is the clearest mover, down 41.6% over the trailing 12 months, 45 incidents against 77 in the prior year, and the single-month drop signal reinforces that longer structural shift. Other larceny has fallen just as sharply, 115 incidents in the current 12 months against 175 the year before, a 34.3% reduction. Vandalism and theft from vehicle are also lower year-over-year, though neither crossed the signal threshold this month. Robbery is the one category moving in the opposite direction, 13 incidents in the current 12 months against 6 prior, but volumes remain low in absolute terms.
Notable signals 1
Motor Vehicle Theft
The past 12 months saw 45 incidents — about 61% below the 114 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 115, down 34% from 175 the year before. If the trend holds another quarter, it will pull the multi-year baseline down.
- Motor Vehicle Theft has reset to a lower baseline.
The trailing 12-month count is 45, down 42% from 77 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 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.
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.
Theft from Vehicle
Vandalism
How Cheesman Park 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.”
Sloan Lake
45 incidents over the past 12 months — 0 below Cheesman Park's 45.
Open page →Valverde
45 incidents over the past 12 months — 0 below Cheesman Park's 45.
Open page →Athmar Park
46 incidents over the past 12 months — 1 above Cheesman Park's 45.
Open page →Recurring local terms (last 12 months)
Top terms in incident descriptions for Cheesman Park, 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 Denver Open Data — DPD's NIBRS-coded crime offenses on ArcGIS Hub — mapped to 9 NIBRS-aligned categories (sexual assault is excluded because DPD redacts victim-bearing rows from the public feed). The feed publishes a 5-year rolling window so the analysis baseline starts at 2021-01. Aggregated to statistical 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.