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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · APRIL 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/april-2025-report
Monthly Traffic Safety Analysis
7,812 CRASHES IN
CONNECTICUT, CT
APRIL 2025
In April 2025, Connecticut recorded 7,812 total traffic crashes, a figure nearly identical to the 7,808 crashes reported in April 2024. Despite this stability in overall crash volume, the number of fatalities increased from 17 to 19 year-over-year. The most significant shift was the increase in hit-and-run incidents, which rose by 10.1% from 957 to 1,054.
7,812
▲ 0.1%was 7,808
Total Crash Events
19
▲ 11.8%was 17
Persons Killed
2,449
▼ -3.0%was 2,524
Persons Injured
1,054
▲ 10.1%was 957
Hit-and-Run Crashes
Note: "Persons Killed" (19) counts individual fatalities across all crash events. "Fatal" in the severity table below (11) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2025-04-01 to 2025-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash volume in Connecticut remained stable between April 2024 and April 2025, with a negligible increase of just four incidents. However, the severity of these crashes shifted, as total fatalities rose by 11.8% from 17 to 19. Conversely, the number of reported injuries declined by 3.0%, falling from 2,524 to 2,449.
1,054
Hit-and-Run Crashes — April 2025
▲ 10.1% vs prior (957)
Hit-and-run crashes increased notably between April 2024 and April 2025. The total number of hit-and-run incidents rose by 10.1%, from 957 to 1,054. This upward trend is also reflected in the hit-and-run rate, which climbed from 12.3% to 13.5% of all crashes, indicating that a larger proportion of crashes involved a driver leaving the scene.
Vulnerable Road User Casualties
2
Pedestrians Killed
1
Cyclists Killed
16
Motorists Killed
83
Pedestrians Injured
31
Cyclists Injured
2,335
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2025-04-01 to 2025-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained broadly consistent year-over-year, with the afternoon commute representing the highest-risk period. The peak day for crashes was Tuesday in both April 2025 (1,368 crashes) and April 2024 (1,363 crashes). While the peak hour shifted slightly from 3 p.m. in the prior year to 4 p.m. in the current period, both hours fall within the consistent afternoon peak. Notably, Monday crashes decreased from 1,300 to 1,027, while Wednesday crashes increased from 1,116 to 1,329.
Source: Connecticut Crash Data · Csv Open Data · 2025-04-01 to 2025-04-30 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2025-04-01 to 2025-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total fatalities increased from 17 to 19, the number of fatal crash events decreased from 17 to 11, indicating more fatalities per fatal crash in April 2025. The overall fatal crash rate, representing the percentage of crashes that were fatal, dropped from 0.22% to 0.14%. Crashes resulting in serious injuries also declined, from 90 incidents (1.2%) in the prior year to 80 incidents (1.0%) in the current period. Correspondingly, the proportion of crashes with no reported injuries increased from 75.9% to 76.7%.
Severity is per crash event (most severe injury). 11 fatal crash events resulted in 19 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2025-04-01 to 2025-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2025-04-01 to 2025-04-30 · Most severe injury per crash record
Road & Environmental Conditions
The vast majority of crashes in both periods occurred in clear weather and on dry roads. In April 2025, 81.9% of crashes happened in clear weather, up from 77.5% in the prior year. Correspondingly, crashes during rain decreased from 1,110 to 810. A similar trend was observed for road surface conditions, with crashes on wet roads declining from 1,395 in April 2024 to 1,191 in April 2025.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2025-04-01 to 2025-04-30 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2025-04-01 to 2025-04-30 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2025-04-01 to 2025-04-30 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes remained consistent, with Honda, Toyota, and Ford being the top three in both periods. Ford-involved crashes saw a notable decrease from 1,350 to 1,201 year-over-year, while Honda and Toyota numbers remained relatively stable. The age distribution of persons involved in crashes also showed little change, though there was a decrease in the 16-20 age group (from 1,829 to 1,736) and a corresponding increase in the 65+ age group (from 2,020 to 2,117).
Top Vehicle Makes (14,860 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2025-04-01 to 2025-04-30 · Vehicle unit records
1,088 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (17,059 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2025-04-01 to 2025-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph zones increased from 2,091 to 2,267, while volumes in other common speed zones remained relatively stable year-over-year. A significant shift occurred in the location of fatal crashes. In April 2024, most fatal crashes happened in higher speed zones, including four in 50 mph zones and three in 65 mph zones. In contrast, April 2025 saw fatal crashes concentrate in lower speed zones, with four occurring in 40 mph zones and three in 30 mph zones.
Fatal crashes by zone: 25 mph: 2 of 2,267 (0.088%) · 30 mph: 3 of 578 (0.519%) · 40 mph: 4 of 426 (0.939%) · 50 mph: 1 of 192 (0.521%) · 65 mph: 1 of 574 (0.174%)
Source: Connecticut Crash Data · Csv Open Data · 2025-04-01 to 2025-04-30 · 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: 2025-04-01 through 2025-04-30
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2025-04-01 through 2025-04-30 (30 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 7,812
- Total persons involved: 18,381
- Total vehicles involved: 14,860
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: April 2025." Published August 20, 2026. Reporting period: 2025-04-01 to 2025-04-30. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/april-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: 2025-04-01 – 2025-04-30
Generated: August 20, 2026 · All rights reserved
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