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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · JANUARY 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/january-2026-report
Monthly Traffic Safety Analysis
9,672 CRASHES IN
CONNECTICUT, CT
JANUARY 2026
In January 2026, there were 9,672 total crashes, a 12.6% increase from the 8,587 crashes recorded in January 2025. Despite the rise in total collisions, the number of fatalities decreased significantly from 22 to 10. The most notable change was a 56.8% increase in crashes where speeding was a contributing factor, rising from 847 to 1,328 incidents year-over-year.
9,672
▲ 12.6%was 8,587
Total Crash Events
10
▼ -54.5%was 22
Persons Killed
2,587
▲ 9.9%was 2,355
Persons Injured
1,289
▲ 17.6%was 1,096
Hit-and-Run Crashes
Note: "Persons Killed" (10) counts individual fatalities across all crash events. "Fatal" in the severity table below (9) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2026-01-01 to 2026-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash trends show an overall increase in collision volume in January 2026 compared to the same month in the prior year. Total crashes rose by 12.6% from 8,587 to 9,672. While total injuries also increased by 9.8% from 2,355 to 2,587, the number of fatalities saw a significant decrease of 54.5%, dropping from 22 to 10 year-over-year.
1,289
Hit-and-Run Crashes — January 2026
▲ 17.6% vs prior (1,096)
The number of hit-and-run incidents increased by 17.6%, rising from 1,096 in January 2025 to 1,289 in January 2026. The hit-and-run rate, which measures the proportion of total crashes that were hit-and-runs, also trended slightly upward. This rate increased from 12.8% in the prior year to 13.3% in the current period.
Vulnerable Road User Casualties
2
Pedestrians Killed
1
Cyclists Killed
7
Motorists Killed
86
Pedestrians Injured
6
Cyclists Injured
2,495
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2026-01-01 to 2026-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal pattern of crashes showed a shift in the peak day of the week, moving from Monday (1,616 crashes) in January 2025 to Thursday (1,739 crashes) in January 2026. The peak hour for collisions remained consistent at 5 p.m. in both periods. However, the number of crashes during that peak hour increased from 724 to 797, reflecting the overall rise in traffic incidents.
Source: Connecticut Crash Data · Csv Open Data · 2026-01-01 to 2026-01-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2026-01-01 to 2026-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The overall severity of crashes decreased in January 2026 compared to the previous year, with the fatal crash rate dropping from 0.23 to 0.09 per 100 crashes. Fatal incidents accounted for 0.1% of all crashes, down from 0.2% in the prior period. The proportion of crashes resulting in no injury increased from 79.0% to 80.2%, while the share of minor injury crashes decreased slightly from 10.0% to 9.2%.
Severity is per crash event (most severe injury). 9 fatal crash events resulted in 10 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2026-01-01 to 2026-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2026-01-01 to 2026-01-31 · Most severe injury per crash record
Road & Environmental Conditions
There was a notable shift in crash conditions, with a higher proportion of incidents occurring on adverse road surfaces in January 2026. The share of crashes on dry roads decreased from 75.1% in the prior year to 61.4% in the current period. Correspondingly, crashes on snow-covered roads more than doubled, increasing from 705 to 1,636 incidents. The distribution of crashes by lighting condition remained relatively stable year-over-year.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2026-01-01 to 2026-01-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2026-01-01 to 2026-01-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2026-01-01 to 2026-01-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes showed a consistent pattern, with Toyota (1,985), Honda (1,978), and Ford (1,597) remaining the top three most frequently involved makes in January 2026, mirroring the previous year. The age distribution of persons involved in collisions also remained largely stable, with the 26-34 and 35-44 age groups consistently representing the largest shares in both periods.
Top Vehicle Makes (17,666 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2026-01-01 to 2026-01-31 · Vehicle unit records
1,397 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (19,921 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2026-01-01 to 2026-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes increased across most speed zones in January 2026, and speeding-related crashes jumped by 56.8% from 847 to 1,328. A notable shift occurred in the location of fatal crashes by speed zone. In the prior period, 7 of 20 fatal crashes occurred in 55 mph or 65 mph zones. In the current period, fatal crashes were more distributed across lower speed zones, with 4 of the 9 fatal crashes occurring in zones posted at 40 mph or less.
Fatal crashes by zone: 25 mph: 2 of 2,808 (0.071%) · 30 mph: 2 of 797 (0.251%) · 40 mph: 2 of 566 (0.353%) · 55 mph: 2 of 853 (0.234%) · 65 mph: 1 of 621 (0.161%)
Source: Connecticut Crash Data · Csv Open Data · 2026-01-01 to 2026-01-31 · 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: 2026-01-01 through 2026-01-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2026-01-01 through 2026-01-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 9,672
- Total persons involved: 21,582
- Total vehicles involved: 17,666
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: January 2026." Published August 20, 2026. Reporting period: 2026-01-01 to 2026-01-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/january-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: 2026-01-01 – 2026-01-31
Generated: August 20, 2026 · All rights reserved
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