City Crime Trajectories
We analyzed multi-year crime trends for 10,509 cities and classified each one into a trajectory type. Is your city getting safer, more dangerous, or bouncing around unpredictably?
Key Insights
- →Of 9,700+ cities analyzed, the vast majority (80%+) are classified as 'stable' — their crime rates aren't changing significantly.
- →Only a handful of cities are 'rapidly improving' or 'rapidly worsening' — extreme change is rare.
- →Trajectory matters more than snapshot: a city at 400/100K and dropping is safer than one at 300/100K and rising.
📈
158
Improving
Crime rates declining consistently over multiple years
📉
302
Worsening
Crime rates increasing consistently over multiple years
📊
3,065
Volatile
Crime rates swinging up and down unpredictably
🛡️
3,303
Stable & Safe
Consistently low crime rates (under 200 violent per 100K)
⚠️
392
Stable & Dangerous
Consistently high crime rates that aren't changing
Trajectory Distribution
📈 Improving Cities (Largest)
| City | Pop. | Violent Rate | YoY Change |
|---|---|---|---|
| Chicago, IL | 2,638,698 | 539.8 | -11.0% |
| Las Vegas Metropolitan Police Department, NV | 1,716,565 | 429.8 | -8.6% |
| San Antonio, TX | 1,514,458 | 594.1 | -14.4% |
| Dallas, TX | 1,321,502 | 658.2 | -2.0% |
| Fort Worth, TX | 997,476 | 458.4 | -6.4% |
| Honolulu, HI | 992,973 | 185.2 | -0.5% |
| Columbus, OH | 915,447 | 434.9 | +12.9% |
| Louisville Metro, KY | 676,843 | 707.4 | -7.6% |
| Detroit, MI | 651,171 | 1781.3 | -13.2% |
| Tucson, AZ | 548,789 | 588.8 | -15.7% |
📉 Worsening Cities (Largest)
| City | Pop. | Violent Rate | YoY Change |
|---|---|---|---|
| New York, NY | 8,299,271 | 671.0 | +0.4% |
| San Jose, CA | 956,840 | 606.8 | +15.1% |
| Seattle, WA | 760,058 | 775.1 | -0.3% |
| Denver, CO | 722,031 | 993.0 | -2.8% |
| Portland, OR | 623,066 | 720.1 | +0.7% |
| Mesa, AZ | 513,585 | 482.7 | +10.9% |
| Colorado Springs, CO | 491,474 | 715.6 | +3.4% |
| Raleigh, NC | 488,085 | 488.8 | -7.4% |
| Long Beach, CA | 444,232 | 676.4 | +8.1% |
| Oakland, CA | 435,042 | 1925.3 | -47.1% |
📊 Volatile Cities (Largest)
| City | Pop. | Violent Rate | YoY Change |
|---|---|---|---|
| Los Angeles, CA | 3,796,352 | 728.5 | -11.2% |
| Houston, TX | 2,319,160 | 1148.2 | +5.2% |
| Phoenix, AZ | 1,662,809 | 799.6 | +1.9% |
| Philadelphia, PA | 1,549,259 | 908.7 | -7.6% |
| San Diego, CA | 1,389,024 | 412.2 | -1.3% |
| Charlotte-Mecklenburg, NC | 1,003,130 | 733.2 | +1.0% |
| Austin, TX | 984,613 | 466.9 | -6.5% |
| Indianapolis, IN | 890,685 | 877.9 | -14.8% |
| San Francisco, CA | 802,856 | 596.5 | -16.0% |
| Oklahoma City, OK | 709,456 | 676.0 | +6.0% |
How We Classify Trajectories
Our trajectory classification uses 3-5 years of FBI Uniform Crime Report data for each city. We analyze year-over-year changes in violent crime rates to determine the overall direction:
- Improving: Violent crime rate has declined every year in the available data period, but the city is still above 200 per 100K.
- Worsening: Violent crime rate has increased every year.
- Stable & Safe: All years show declining rates AND the latest rate is under 200 per 100K — consistently low.
- Stable & Dangerous: All years show increasing rates AND the latest rate exceeds 500 per 100K — stuck in a high-crime pattern.
- Volatile: Crime rates bounce up and down with no clear trend — the most common pattern, reflecting how crime responds to many variables.
Volatility is the most common trajectory (3,065 cities) because crime rates are influenced by many factors: policing changes, economic shifts, drug markets, and even weather. A single year's spike or drop often reverses the next year.
Demographic context: Crime trajectory improvements benefit all communities, but historically disadvantaged neighborhoods may lag. National data shows significant racial disparities in victimization. Arrest demographics | Racial disparities