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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · FEBRUARY 2026
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/february-2026-report
Monthly Traffic Safety Analysis
8,417 CRASHES IN
CONNECTICUT, CT
FEBRUARY 2026
In February 2026, there were 8,417 total crashes, a 5.5% increase from the 7,979 crashes recorded in February 2025. Despite the rise in total collisions, the number of fatalities decreased from 8 to 6 year-over-year. One of the most notable shifts was a 25.7% decrease in speeding-related crashes, which fell from 1,262 to 938.
8,417
▲ 5.5%was 7,979
Total Crash Events
6
▼ -25.0%was 8
Persons Killed
2,145
▲ 2.4%was 2,094
Persons Injured
1,081
▲ 13.9%was 949
Hit-and-Run Crashes
Note: "Persons Killed" (6) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2026-02-01 to 2026-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends show an increase in collision volume compared to the same period last year. Total crashes rose by 5.5%, from 7,979 to 8,417. While total injuries also saw a slight increase of 2.4% (from 2,094 to 2,145), the number of fatalities declined from 8 to 6.
1,081
Hit-and-Run Crashes — February 2026
▲ 13.9% vs prior (949)
Hit-and-run incidents increased in both count and proportion compared to the previous year. The number of hit-and-run crashes rose from 949 to 1,081. This represents an increase in the hit-and-run rate from 11.9% of all crashes in February 2025 to 12.8% in February 2026, indicating an upward trend.
Vulnerable Road User Casualties
2
Pedestrians Killed
0
Cyclists Killed
4
Motorists Killed
70
Pedestrians Injured
5
Cyclists Injured
2,070
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2026-02-01 to 2026-02-28 · 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 Friday being the peak day for collisions in both February 2026 (1,367 crashes) and February 2025 (1,283 crashes). However, the peak hour for crashes shifted slightly earlier, from 4 PM in the prior year to 3 PM in the current period. Crashes during the morning commute hours of 7 AM to 9 AM increased from 961 to 1,162 year-over-year.
Source: Connecticut Crash Data · Csv Open Data · 2026-02-01 to 2026-02-28 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2026-02-01 to 2026-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The fatal crash rate increased from 0.06 to 0.07 per 100 crashes year-over-year, with the count of fatal crashes rising from 5 to 6. The proportion of crashes resulting in serious injuries also grew, from 0.7% to 0.9% of all incidents. Meanwhile, the share of crashes involving minor or possible injuries saw a slight decrease, from a combined 19.2% in the prior period to 17.8% in the current period.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2026-02-01 to 2026-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2026-02-01 to 2026-02-28 · Most severe injury per crash record
Road & Environmental Conditions
The proportion of crashes occurring in clear weather increased from 74.2% to 78.3% year-over-year, while crashes during snowy conditions decreased from 1,053 to 848. The distribution of crashes by lighting conditions remained relatively stable, with about two-thirds of incidents in both periods occurring during daylight hours. Road surface conditions also showed little change, with crashes on dry roads accounting for 67.8% of the total in the current period compared to 65.9% in the prior year.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2026-02-01 to 2026-02-28 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2026-02-01 to 2026-02-28 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2026-02-01 to 2026-02-28 · Road surface condition field
Vehicles & Demographics
Toyota and Honda were the top two vehicle makes involved in crashes, swapping the first and second positions year-over-year; Toyota-involved crashes increased from 1,566 to 1,742, while Honda-involved crashes rose from 1,588 to 1,736. The top three makes, including Ford, remained consistent between the two periods. Analysis of persons involved shows a shift in age distribution, with the 35-44 age group's representation increasing from 16.3% to 17.6% of all individuals involved in crashes.
Top Vehicle Makes (15,760 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2026-02-01 to 2026-02-28 · Vehicle unit records
1,328 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (17,885 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2026-02-01 to 2026-02-28 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph zones increased from 2,217 to 2,619, while collisions in 55 mph and 65 mph zones decreased from a combined 1,443 to 1,141. There was a notable shift in where fatal crashes occurred. In the prior year, fatalities were recorded in zones of 35 mph or less, with one at 55 mph. In the current year, four of the six fatal crashes occurred in zones with speed limits of 45 mph or higher.
Fatal crashes by zone: 25 mph: 1 of 2,619 (0.038%) · 45 mph: 2 of 300 (0.667%) · 50 mph: 1 of 194 (0.515%) · 55 mph: 1 of 599 (0.167%) · 65 mph: 1 of 542 (0.185%)
Source: Connecticut Crash Data · Csv Open Data · 2026-02-01 to 2026-02-28 · 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: 2026-02-01 through 2026-02-28
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2026-02-01 through 2026-02-28 (28 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 8,417
- Total persons involved: 19,437
- Total vehicles involved: 15,760
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: February 2026." Published August 20, 2026. Reporting period: 2026-02-01 to 2026-02-28. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/february-2026-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: 2026-02-01 – 2026-02-28
Generated: August 20, 2026 · All rights reserved
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