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ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · MAY 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/may-2025-report
Monthly Traffic Safety Analysis
8,778 CRASHES IN
CONNECTICUT, CT
MAY 2025
In May 2025, Connecticut recorded 8,778 traffic crashes, a 4.6% decrease from the 9,200 crashes reported in May 2024. Overall, the data indicates a general improvement in road safety outcomes compared to the previous year. The most significant year-over-year change was a 37% reduction in total fatalities, which fell from 27 in May 2024 to 17 in May 2025.
8,778
▼ -4.6%was 9,200
Total Crash Events
17
▼ -37.0%was 27
Persons Killed
2,737
▼ -11.6%was 3,097
Persons Injured
1,141
▼ -4.5%was 1,195
Hit-and-Run Crashes
Note: "Persons Killed" (17) counts individual fatalities across all crash events. "Fatal" in the severity table below (17) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic safety metrics showed a positive trend in May 2025 compared to the same month in the prior year. Total crashes decreased by 4.6%, from 9,200 to 8,778. This downward trend was also reflected in the number of people harmed, with total injuries declining by 11.6% and fatalities dropping by 37%.
1,141
Hit-and-Run Crashes — May 2025
▼ -4.5% vs prior (1,195)
The rate of hit-and-run incidents remained stable year-over-year, holding at 13% of all crashes in both May 2025 and May 2024. The absolute number of hit-and-run crashes saw a slight decrease, falling from 1,195 in the prior period to 1,141 in the current period. This indicates that while overall crashes declined, the proportion of drivers leaving the scene of a collision did not change.
Vulnerable Road User Casualties
2
Pedestrians Killed
1
Cyclists Killed
14
Motorists Killed
73
Pedestrians Injured
28
Cyclists Injured
2,636
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2025-05-01 to 2025-05-31 · 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 May 2025 (1,596 crashes) and May 2024 (1,687 crashes). However, the peak hour for crashes shifted slightly earlier, moving from 4 PM in the prior year (838 crashes) to 3 PM in the current period (791 crashes). While Friday and Thursday were consistently high-volume crash days, crashes on Saturdays increased from 1,105 to 1,414, while Wednesday crashes decreased from 1,601 to 1,077.
Source: Connecticut Crash Data · Csv Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes decreased in May 2025 compared to the previous year. The number of fatal crashes fell from 23 to 17, and the fatal crash rate per 100 crashes dropped from 0.25 to 0.19. The proportion of crashes resulting in any type of injury (serious, minor, or possible) also saw a slight decline from 24.2% to 22.8% of all incidents. Correspondingly, crashes resulting in no injuries increased, accounting for 77.0% of all collisions, up from 75.5% in May 2024.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record
Road & Environmental Conditions
While lighting conditions for crashes remained consistent year-over-year, with about 79.5% occurring in daylight, there was a notable shift in weather and road surface conditions. The proportion of crashes happening in the rain increased substantially, from 10.8% in May 2024 to 19.6% in May 2025. This corresponds with a significant rise in collisions on wet road surfaces, which accounted for 25.0% of all crashes in the current period, nearly double the 13.6% reported in the prior year.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes showed minor changes, with Toyota (1,826 vehicles) overtaking Honda (1,797 vehicles) for the most frequently involved make in May 2025; in the prior year, Honda led with 1,955 vehicles. The top five most common makes remained the same across both periods. The age distribution of persons involved in crashes was also stable, with the 26-34 age group consistently being the largest single cohort involved in collisions.
Top Vehicle Makes (16,710 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records
1,295 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (19,514 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2025-05-01 to 2025-05-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones saw minor fluctuations, with a slight decrease in crashes in 25 mph zones (from 2,618 to 2,563) and a small increase in 55 mph zones (from 864 to 913). A more significant shift occurred in the location of fatal crashes. In May 2025, the 40 mph zone was the deadliest, with 5 fatalities, a sharp increase from just 1 fatality in the same zone the prior year. Conversely, fatalities in 25 mph zones dropped dramatically from 9 in May 2024 to 2 in May 2025.
Fatal crashes by zone: 25 mph: 2 of 2,563 (0.078%) · 30 mph: 2 of 673 (0.297%) · 35 mph: 2 of 936 (0.214%) · 40 mph: 5 of 503 (0.994%) · 50 mph: 3 of 244 (1.23%) · 55 mph: 1 of 913 (0.11%) · 65 mph: 1 of 576 (0.174%) · 88 mph: 1 of 366 (0.273%)
Source: Connecticut Crash Data · Csv Open Data · 2025-05-01 to 2025-05-31 · 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: 2025-05-01 through 2025-05-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2025-05-01 through 2025-05-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 8,778
- Total persons involved: 21,034
- Total vehicles involved: 16,710
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: May 2025." Published August 20, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/may-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: 2025-05-01 – 2025-05-31
Generated: August 20, 2026 · All rights reserved
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