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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · JANUARY 2025
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/connecticut/statewide/january-2025-report
Monthly Traffic Safety Analysis
8,587 CRASHES IN
CONNECTICUT, CT
JANUARY 2025
In January 2025, Connecticut recorded 8,587 total crashes, a 3.1% decrease from the 8,858 crashes documented in January 2024. While overall crashes, injuries, and fatalities declined, the most notable year-over-year change was a 37.4% reduction in crashes where speeding was a factor, which fell from 1,353 to 847.
8,587
▼ -3.1%was 8,858
Total Crash Events
22
▼ -15.4%was 26
Persons Killed
2,355
▼ -7.1%was 2,534
Persons Injured
1,096
▲ 8.5%was 1,010
Hit-and-Run Crashes
Note: "Persons Killed" (22) counts individual fatalities across all crash events. "Fatal" in the severity table below (20) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic safety metrics showed a general improvement in January 2025 compared to the same month in the prior year. Total crashes decreased by 3.1%, from 8,858 to 8,587. This downward trend was also reflected in casualties, with total fatalities falling from 26 to 22 and total injuries decreasing from 2,534 to 2,355.
1,096
Hit-and-Run Crashes — January 2025
▲ 8.5% vs prior (1,010)
Hit-and-run incidents increased in both count and rate when comparing January 2025 to the previous year. The number of hit-and-run crashes rose from 1,010 to 1,096. This represents an upward trend in the hit-and-run rate, which increased from 11.4% of all crashes in January 2024 to 12.8% in January 2025.
Vulnerable Road User Casualties
4
Pedestrians Killed
0
Cyclists Killed
18
Motorists Killed
95
Pedestrians Injured
9
Cyclists Injured
2,251
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed some shifts between January 2024 and January 2025. The peak day for crashes moved from Tuesday (1,680 crashes) in the prior year to Monday (1,616 crashes) in the current period. However, the peak hour for collisions remained consistent at 5 PM in both years, with a slight decrease in crash volume from 780 to 724 during that hour.
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-01-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes saw a slight decrease year-over-year. The fatal crash rate fell from 0.26% in January 2024 to 0.23% in January 2025, with 20 fatal crashes recorded in the current period compared to 23 in the prior. The proportion of crashes resulting in any level of injury (Serious, Minor, or Possible) also decreased slightly from 21.1% to 20.7% of all incidents.
Severity is per crash event (most severe injury). 20 fatal crash events resulted in 22 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-01-31 · Most severe injury per crash record
Road & Environmental Conditions
Crash conditions varied significantly year-over-year, largely reflecting different weather patterns. In January 2025, a much higher proportion of crashes occurred on Dry road surfaces (75.1%) and in Clear weather (80.2%), compared to 59.9% and 66.2% respectively in January 2024. Consequently, the share of crashes on Wet surfaces dropped from 18.6% to 8.9%, and those in Snow conditions fell from 12.7% to 9.7%.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-01-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-01-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-01-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes remained consistent year-over-year. In January 2025, the most common makes were Toyota (1,760), Honda (1,742), and Ford (1,392), which is a slight reordering from the prior year when Honda (1,816) led Toyota (1,780). The age demographics of persons involved in crashes also showed little change, with the 26-34 and 35-44 age groups consistently representing the largest shares in both periods.
Top Vehicle Makes (15,980 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-01-31 · Vehicle unit records
1,213 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (18,660 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-01-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones showed some changes year-over-year. There was a notable decrease in crashes within 65 mph zones, falling from 679 to 533. The most significant change was observed in the fatality data for 25 mph zones, where the number of fatal crashes dropped from 8 to just 1. Conversely, while total crashes in 65 mph zones decreased, the fatal crash rate within that zone increased from 0.442% to 0.75%.
Fatal crashes by zone: 1 mph: 2 of 1,031 (0.194%) · 25 mph: 1 of 2,545 (0.039%) · 30 mph: 2 of 719 (0.278%) · 35 mph: 3 of 1,008 (0.298%) · 40 mph: 1 of 502 (0.199%) · 45 mph: 3 of 341 (0.88%) · 50 mph: 1 of 231 (0.433%) · 55 mph: 3 of 719 (0.417%) · 65 mph: 4 of 533 (0.75%)
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-01-31 · Posted speed limit at crash location
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Connecticut Crash Data, accessed programmatically via the Csv Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.
Data Retrieval
- Access method: Csv Open Data API (SoQL queries)
- Data format: Structured JSON via REST API
- Record types queried: Crash events, person records, and vehicle unit records
- Date filter applied: 2025-01-01 through 2025-01-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-01-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 8,587
- Total persons involved: 20,094
- Total vehicles involved: 15,980
Analytical Methodology
- Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
- Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
- Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
- Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
- Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
- Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
- AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.
Limitations & Disclaimers
- Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
- Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
- Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
- AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
- Percentages are calculated from reported data and are subject to rounding.
Non-Affiliation Disclosure
This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.
Data License
The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.
Corrections & Feedback
If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.
Suggested Citation
ThatCarHitMe.com (Injuria.ai). "connecticut, CT Crash Intelligence Report: January 2025." Published August 20, 2026. Reporting period: 2025-01-01 to 2025-01-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/january-2025-report
About the Publisher
ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.
Questions about this report's data or methodology: data@injuria.ai
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Connecticut Crash Data · Csv
Period: 2025-01-01 – 2025-01-31
Generated: August 20, 2026 · All rights reserved
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