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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · SEPTEMBER 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/september-2025-report
Monthly Traffic Safety Analysis
8,595 CRASHES IN
CONNECTICUT, CT
SEPTEMBER 2025
In September 2025, Connecticut recorded 8,595 traffic crashes, a 1.2% increase from the 8,490 crashes in September 2024. While total injuries decreased by 4.1%, the number of pedestrian fatalities saw a significant year-over-year increase, rising from one to seven.
8,595
▲ 1.2%was 8,490
Total Crash Events
26
▲ 4.0%was 25
Persons Killed
2,762
▼ -4.1%was 2,881
Persons Injured
1,077
▼ -2.0%was 1,099
Hit-and-Run Crashes
Note: "Persons Killed" (26) counts individual fatalities across all crash events. "Fatal" in the severity table below (24) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2025-09-01 to 2025-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends were relatively stable, with total collisions rising by a modest 1.2% from 8,490 in September 2024 to 8,595 in September 2025. During this same period, the number of people injured in crashes decreased by 4.1% (from 2,881 to 2,762), while fatalities increased slightly from 25 to 26.
1,077
Hit-and-Run Crashes — September 2025
▼ -2.0% vs prior (1,099)
Hit-and-run crashes showed a slight downward trend. The total number of hit-and-run incidents decreased from 1,099 in September 2024 to 1,077 in September 2025. The hit-and-run rate, as a percentage of all crashes, also declined modestly from 12.9% to 12.5%.
Vulnerable Road User Casualties
7
Pedestrians Killed
0
Cyclists Killed
19
Motorists Killed
0
Other Killed
119
Pedestrians Injured
40
Cyclists Injured
2,602
Motorists Injured
1
Other Injured
Source: Connecticut Crash Data · Csv Open Data · 2025-09-01 to 2025-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal pattern of crashes shifted this year, with Tuesday replacing Friday as the peak day for collisions (1,473 crashes vs. 1,331 last year). The peak hour for crashes also shifted slightly later, from 3 p.m. in the prior year (759 crashes) to 4 p.m. in the current period (766 crashes), indicating a consistent afternoon rush hour peak.
Source: Connecticut Crash Data · Csv Open Data · 2025-09-01 to 2025-09-30 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2025-09-01 to 2025-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity levels remained broadly consistent year-over-year. The fatal crash rate saw a marginal increase from 0.27% to 0.28%. The proportion of crashes involving any level of injury (Serious, Minor, or Possible) decreased slightly from 24.5% in September 2024 to 23.7% in September 2025, with a corresponding increase in the share of no-injury crashes from 75.1% to 76.0%.
Severity is per crash event (most severe injury). 24 fatal crash events resulted in 26 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2025-09-01 to 2025-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2025-09-01 to 2025-09-30 · Most severe injury per crash record
Road & Environmental Conditions
The environmental conditions at the time of crashes were largely unchanged between the two periods. In both September 2025 and 2024, approximately 91% of crashes occurred on dry roads and 90% happened in clear weather. Similarly, about 75% of collisions in both years took place during daylight hours, showing no significant year-over-year shift in the prevalence of adverse condition-related crashes.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2025-09-01 to 2025-09-30 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2025-09-01 to 2025-09-30 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2025-09-01 to 2025-09-30 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained consistent, though their order shifted; Honda (1,848 vehicles) surpassed Toyota (1,789) for the top spot this year, while Ford (1,350) remained third. The demographic profile of persons involved in crashes also showed stability, with no significant changes in the proportional representation of any age group compared to the previous year.
Top Vehicle Makes (16,345 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2025-09-01 to 2025-09-30 · Vehicle unit records
1,243 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (19,032 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2025-09-01 to 2025-09-30 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones was similar to the prior year, with 25 mph zones hosting the most incidents in both periods (2,430 vs. 2,435). However, the fatal crash rate within 25 mph zones increased significantly, from 0.16% in September 2024 to 0.41% in September 2025. Conversely, the fatal crash rate in 40 mph zones dropped from 0.98% to 0.21%.
Fatal crashes by zone: 25 mph: 10 of 2,430 (0.412%) · 30 mph: 1 of 637 (0.157%) · 35 mph: 5 of 999 (0.501%) · 40 mph: 1 of 483 (0.207%) · 45 mph: 1 of 314 (0.318%) · 55 mph: 3 of 805 (0.373%) · 65 mph: 3 of 577 (0.52%)
Source: Connecticut Crash Data · Csv Open Data · 2025-09-01 to 2025-09-30 · 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: 2025-09-01 through 2025-09-30
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2025-09-01 through 2025-09-30 (30 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 8,595
- Total persons involved: 20,611
- Total vehicles involved: 16,345
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: September 2025." Published August 20, 2026. Reporting period: 2025-09-01 to 2025-09-30. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/september-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: 2025-09-01 – 2025-09-30
Generated: August 20, 2026 · All rights reserved
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