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ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · 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/2025-annual-report
Yearly Traffic Safety Analysis
29,549 CRASHES IN
CONNECTICUT, CT
2025
In New Haven County, total traffic crashes increased by 1.4% from 29,129 in 2024 to 29,549 in 2025. Despite the rise in overall collisions, the number of resulting fatalities saw a notable year-over-year decrease. Total fatalities fell 11.1%, from 81 in the prior period to 72 in the current period, marking the most significant shift in outcomes.
29,549
▲ 1.4%was 29,129
Total Crash Events
72
▼ -11.1%was 81
Persons Killed
9,347
▼ -2.9%was 9,630
Persons Injured
4,265
▲ 3.9%was 4,105
Hit-and-Run Crashes
Note: "Persons Killed" (72) counts individual fatalities across all crash events. "Fatal" in the severity table below (63) 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 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic safety data for New Haven County indicates a slight upward trend in the total number of crashes, which increased by 420 incidents (1.4%) from 2024 to 2025. However, this was accompanied by a positive trend in crash severity, as total fatalities decreased from 81 to 72 (-11.1%) and total injuries fell from 9,630 to 9,347 (-2.9%) over the same period.
4,265
Hit-and-Run Crashes — 2025
▲ 3.9% vs prior (4,105)
Hit-and-run crashes trended upward, with the total count increasing from 4,105 in the prior year to 4,265 in the current year. This change reflects a rise in both the absolute number of such incidents and their relative frequency. Consequently, the hit-and-run rate as a percentage of all crashes grew slightly from 14.1% to 14.4%.
Vulnerable Road User Casualties
15
Pedestrians Killed
0
Cyclists Killed
57
Motorists Killed
0
Other Killed
335
Pedestrians Injured
106
Cyclists Injured
8,904
Motorists Injured
2
Other Injured
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Temporal crash patterns remained largely consistent year-over-year, with Friday continuing to be the day with the highest crash volume in both periods (4,890 in 2025 vs. 4,734 in 2024). A minor shift occurred in the peak hour for collisions, moving from 3 PM in the prior year (2,456 crashes) to 4 PM in the current year (2,478 crashes). The afternoon commute hours consistently represent the time with the highest frequency of incidents.
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes generally decreased compared to the prior year. The number of fatal crashes fell from 72 to 63, and the fatal crash rate per 100 crashes dropped from 0.25 to 0.21. Crashes involving any level of injury—serious, minor, or possible—all decreased as a proportion of total incidents. Correspondingly, crashes resulting in no injuries increased their share of the total, rising from 75.5% to 76.5%.
Severity is per crash event (most severe injury). 63 fatal crash events resulted in 72 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Road & Environmental Conditions
The vast majority of crashes in both periods occurred in clear weather and on dry road surfaces, with the proportions of these conditions remaining stable year-over-year. However, there was a distinct increase in crashes related to adverse winter weather. The number of collisions on roads with snow, ice, or slush rose from 796 to 1,409, and crashes reported during snowy weather increased from 530 to 882.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in collisions were consistent across both periods, with Honda and Toyota leading in both years. A minor change in the rankings occurred as Ford (4,560 vehicles) and Nissan (4,528 vehicles) swapped the third and fourth positions. The 26-34 age group remained the most frequently involved demographic in crashes, with its count increasing from 12,050 to 12,429, while involvement for persons aged 16-25 decreased.
Top Vehicle Makes (56,807 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
4,832 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (65,734 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
Roads with a 25 mph speed limit continued to see the highest number of crashes, with incidents increasing from 10,350 to 10,472. There was also a notable increase in crashes within 55 mph zones, which rose from 3,516 to 3,811. While fatalities decreased in lower speed zones, such as the 25 mph zone where they fell from 28 to 24, the number of fatalities in 55 mph zones increased from 4 to 7 year-over-year.
Fatal crashes by zone: 25 mph: 24 of 10,472 (0.229%) · 30 mph: 3 of 1,792 (0.167%) · 35 mph: 7 of 2,364 (0.296%) · 40 mph: 7 of 1,224 (0.572%) · 45 mph: 8 of 822 (0.973%) · 55 mph: 7 of 3,811 (0.184%) · 65 mph: 7 of 1,612 (0.434%)
Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · 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 2025-12-31
- Report generated: August 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 29,549
- Total persons involved: 71,541
- Total vehicles involved: 56,807
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: 2025." Published August 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/2025-annual-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 – 2025-12-31
Generated: August 21, 2026 · All rights reserved
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