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ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · JUNE 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/june-2025-report
Monthly Traffic Safety Analysis
8,666 CRASHES IN
CONNECTICUT, CT
JUNE 2025
In June 2025, Connecticut recorded 8,666 total crashes, a 3.3% decrease from the 8,964 crashes reported in June 2024. The most significant year-over-year change was a substantial 61.5% reduction in total fatalities, which fell from 39 to 15.
8,666
▼ -3.3%was 8,964
Total Crash Events
15
▼ -61.5%was 39
Persons Killed
2,963
▼ -3.1%was 3,059
Persons Injured
1,127
▼ -0.5%was 1,133
Hit-and-Run Crashes
Note: "Persons Killed" (15) counts individual fatalities across all crash events. "Fatal" in the severity table below (15) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2025-06-01 to 2025-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crash trends in Connecticut showed a decline in June 2025 compared to the same month in the prior year. Total crashes decreased by 3.3% from 8,964 to 8,666, and total injuries saw a similar 3.1% drop from 3,059 to 2,963. The most dramatic change was a 61.5% decrease in fatalities, from 39 in June 2024 to 15 in June 2025.
1,127
Hit-and-Run Crashes — June 2025
▼ -0.5% vs prior (1,133)
The number of hit-and-run incidents remained nearly stable, with 1,127 crashes in June 2025 compared to 1,133 in June 2024. However, because the total number of crashes decreased year-over-year, the hit-and-run rate saw a slight increase. Hit-and-runs accounted for 13.0% of all crashes in the current period, up from 12.6% in the prior period.
Vulnerable Road User Casualties
2
Pedestrians Killed
0
Cyclists Killed
13
Motorists Killed
0
Other Killed
70
Pedestrians Injured
31
Cyclists Injured
2,861
Motorists Injured
1
Other Injured
Source: Connecticut Crash Data · Csv Open Data · 2025-06-01 to 2025-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed a shift in the peak day of the week between the two periods. In June 2025, Monday was the day with the most crashes (1,460), whereas in June 2024, Saturday saw the highest volume (1,425). The peak hour for crashes remained consistent at 4 p.m. in both years, although the number of crashes during that hour decreased from 794 to 732.
Source: Connecticut Crash Data · Csv Open Data · 2025-06-01 to 2025-06-30 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2025-06-01 to 2025-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes improved significantly year-over-year. The number of fatal crashes dropped from 35 in June 2024 to 15 in June 2025, and their proportion of all crashes fell from 0.4% to 0.2%. The proportion of crashes resulting in serious injuries saw a slight increase from 1.4% to 1.6% of total incidents, while the share of crashes with minor or no injuries remained relatively stable.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2025-06-01 to 2025-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2025-06-01 to 2025-06-30 · Most severe injury per crash record
Road & Environmental Conditions
The distribution of crashes across different conditions shifted slightly year-over-year. While crashes on dry roads and in clear weather remained the majority, their share of total crashes decreased. In June 2025, 8.3% of crashes occurred during rain, up from 5.4% in June 2024. Similarly, crashes on wet road surfaces increased from 7.4% to 11.9% of the total, while lighting conditions for crashes remained largely consistent between the two periods.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2025-06-01 to 2025-06-30 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2025-06-01 to 2025-06-30 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2025-06-01 to 2025-06-30 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes remained consistent, with Honda, Toyota, and Ford being the most common in both June 2025 and June 2024, though their counts decreased slightly. The total number of vehicles involved decreased from 16,977 to 16,620. Analysis of persons involved in crashes shows a stable age distribution, although there was a slight proportional increase in individuals aged 65 and older, from 11.2% of persons in the prior period to 11.9% in the current period.
Top Vehicle Makes (16,620 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2025-06-01 to 2025-06-30 · Vehicle unit records
1,247 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (19,526 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2025-06-01 to 2025-06-30 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones remained largely similar year-over-year, with a slight decrease in incidents occurring in zones of 55 mph or higher. A significant change was observed in the 25 mph speed zone, where fatalities dropped from 13 in June 2024 to just 1 in June 2025, despite a similar number of crashes. Conversely, in the 55 mph zone, fatalities increased from 0 to 3, even as the total number of crashes in that zone decreased.
Fatal crashes by zone: 25 mph: 1 of 2,494 (0.04%) · 30 mph: 3 of 663 (0.452%) · 35 mph: 2 of 954 (0.21%) · 45 mph: 2 of 294 (0.68%) · 50 mph: 1 of 236 (0.424%) · 55 mph: 3 of 898 (0.334%) · 65 mph: 1 of 573 (0.175%) · 88 mph: 1 of 328 (0.305%) · 99 mph: 1 of 66 (1.515%)
Source: Connecticut Crash Data · Csv Open Data · 2025-06-01 to 2025-06-30 · 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: 2025-06-01 through 2025-06-30
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2025-06-01 through 2025-06-30 (30 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 8,666
- Total persons involved: 20,995
- Total vehicles involved: 16,620
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: June 2025." Published August 20, 2026. Reporting period: 2025-06-01 to 2025-06-30. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/june-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: 2025-06-01 – 2025-06-30
Generated: August 20, 2026 · All rights reserved
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