If you're a data point in this report, call us.
We'll evaluate whether you have a case. Free, and no pressure.
ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · MARCH 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/march-2025-report
Monthly Traffic Safety Analysis
7,435 CRASHES IN
CONNECTICUT, CT
MARCH 2025
In March 2025, Connecticut recorded 7,435 total vehicle crashes, a 6% decrease from the 7,913 crashes documented in March 2024. This overall decline was accompanied by a 13.6% drop in fatalities, from 22 to 19, and a 5.1% reduction in injuries. One of the most notable shifts was observed in crash conditions, with crashes during rainy weather decreasing from 1,498 to 620, a drop of over 58% year-over-year.
7,435
▼ -6.0%was 7,913
Total Crash Events
19
▼ -13.6%was 22
Persons Killed
2,303
▼ -5.1%was 2,426
Persons Injured
997
▼ -9.4%was 1,100
Hit-and-Run Crashes
Note: "Persons Killed" (19) counts individual fatalities across all crash events. "Fatal" in the severity table below (18) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2025-03-01 to 2025-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic safety metrics showed a general improvement in March 2025 compared to the same month in the prior year. Total crashes fell by 6.0% from 7,913 to 7,435. Similarly, the number of individuals injured in these incidents decreased by 5.1% to 2,303, and fatalities declined by 13.6% from 22 to 19.
997
Hit-and-Run Crashes — March 2025
▼ -9.4% vs prior (1,100)
The number of hit-and-run incidents decreased in March 2025 compared to the same month a year prior. There were 997 hit-and-run crashes, down 9.4% from 1,100 in March 2024. The hit-and-run rate, representing the proportion of all crashes that were hit-and-runs, also saw a slight decline, falling from 13.9% to 13.4%.
Vulnerable Road User Casualties
4
Pedestrians Killed
1
Cyclists Killed
14
Motorists Killed
76
Pedestrians Injured
19
Cyclists Injured
2,208
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2025-03-01 to 2025-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. In March 2025, Monday was the peak day for crashes with 1,216 incidents, a change from March 2024 when Friday was the busiest day with 1,441 crashes. The peak hour also moved slightly later in the day, from 3 p.m. in the prior year (703 crashes) to 4 p.m. in the current period (660 crashes).
Source: Connecticut Crash Data · Csv Open Data · 2025-03-01 to 2025-03-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2025-03-01 to 2025-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The overall severity of crashes saw a slight decrease in March 2025 compared to March 2024. The number of fatal crashes dropped from 22 to 18, and the fatal crash rate per 100 crashes decreased from 0.28 to 0.24. While the proportion of serious injury crashes remained stable at 1.0% in both periods, the share of crashes resulting in minor injuries increased slightly from 10.9% to 11.1%.
Severity is per crash event (most severe injury). 18 fatal crash events resulted in 19 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2025-03-01 to 2025-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2025-03-01 to 2025-03-31 · Most severe injury per crash record
Road & Environmental Conditions
Crash conditions improved significantly in March 2025 compared to the previous year, largely due to different weather patterns. Crashes on wet road surfaces decreased by 43.3% (from 1,735 to 984), and collisions during rainy weather fell by 58.6% (from 1,498 to 620). Consequently, the proportion of crashes occurring on dry roads under clear skies increased, with dry surface crashes making up 85.7% of the total, up from 76.4% in the prior year. Crashes in daylight conditions made up 72.9% of all incidents, a slight increase from 70.3% in March 2024.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2025-03-01 to 2025-03-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2025-03-01 to 2025-03-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2025-03-01 to 2025-03-31 · Road surface condition field
Vehicles & Demographics
The distribution of vehicle makes involved in crashes remained largely consistent year-over-year. In March 2025, the top three makes were Toyota (1,561 vehicles), Honda (1,553), and Ford (1,193), a slight shuffle from the prior year when Honda led with 1,657 vehicles. An analysis of persons involved in crashes shows a consistent age distribution, with the 26-34 and 35-44 age groups representing the largest shares in both periods, accounting for 2,859 and 2,858 individuals respectively in the current year.
Top Vehicle Makes (14,178 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2025-03-01 to 2025-03-31 · Vehicle unit records
1,145 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (16,339 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2025-03-01 to 2025-03-31 · Person-level records linked to crash events
Speed Limit Zones
In March 2025, the distribution of crashes across different speed zones remained concentrated in lower-speed areas, with 25 mph zones accounting for the most incidents (2,182 crashes), similar to the prior year. However, the number of fatal crashes in these 25 mph zones increased from 6 to 8 year-over-year. In contrast, higher-speed zones saw a reduction in fatalities; there were zero fatal crashes in 65 mph zones, down from 5 in March 2024.
Fatal crashes by zone: 25 mph: 8 of 2,182 (0.367%) · 30 mph: 2 of 531 (0.377%) · 35 mph: 2 of 822 (0.243%) · 40 mph: 1 of 437 (0.229%) · 45 mph: 4 of 276 (1.449%) · 55 mph: 1 of 728 (0.137%)
Source: Connecticut Crash Data · Csv Open Data · 2025-03-01 to 2025-03-31 · 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: 2025-03-01 through 2025-03-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2025-03-01 through 2025-03-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 7,435
- Total persons involved: 17,630
- Total vehicles involved: 14,178
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: March 2025." Published August 20, 2026. Reporting period: 2025-03-01 to 2025-03-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/march-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: 2025-03-01 – 2025-03-31
Generated: August 20, 2026 · All rights reserved
The data is step one. Get a Connecticut attorney on the line.
Call our intake team. We connect you to a vetted Connecticut personal injury attorney who calls you back within minutes. No phone tag. No voicemails.
Always free for accident victims.