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ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · OCTOBER 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/october-2025-report
Monthly Traffic Safety Analysis
9,535 CRASHES IN
CONNECTICUT, CT
OCTOBER 2025
In October 2025, Connecticut recorded 9,535 vehicle crashes, a marginal 0.9% increase from the 9,449 crashes in October 2024. While the total number of crashes remained relatively stable, the state saw a significant year-over-year decrease in traffic fatalities, which fell by 34.2% from 38 to 25.
9,535
▲ 0.9%was 9,449
Total Crash Events
25
▼ -34.2%was 38
Persons Killed
2,957
▼ -5.3%was 3,121
Persons Injured
1,168
▲ 2.3%was 1,142
Hit-and-Run Crashes
Note: "Persons Killed" (25) counts individual fatalities across all crash events. "Fatal" in the severity table below (20) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2025-10-01 to 2025-10-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends for October 2025 show a nearly stable volume compared to the same month in the prior year, with total incidents increasing by just 86 to 9,535. Despite this, outcomes improved, as total injuries decreased by 5.3% from 3,121 to 2,957, and total fatalities saw a substantial 34.2% drop from 38 to 25.
1,168
Hit-and-Run Crashes — October 2025
▲ 2.3% vs prior (1,142)
Hit-and-run incidents remained a consistent issue, showing a slight increase year-over-year. The total number of hit-and-run crashes rose from 1,142 in October 2024 to 1,168 in October 2025. This corresponds to a minor increase in the hit-and-run rate, which edged up from 12.1% to 12.2% of all crashes.
Vulnerable Road User Casualties
3
Pedestrians Killed
0
Cyclists Killed
22
Motorists Killed
137
Pedestrians Injured
40
Cyclists Injured
2,780
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2025-10-01 to 2025-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted slightly year-over-year. The peak day for crashes moved from Thursday (1,634 crashes) in the prior period to Friday (1,853 crashes) in the current period. The peak hour for collisions remained in the afternoon commute but shifted one hour later, from the 3 PM hour (850 crashes) in October 2024 to the 4 PM hour (845 crashes) in October 2025.
Source: Connecticut Crash Data · Csv Open Data · 2025-10-01 to 2025-10-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2025-10-01 to 2025-10-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity outcomes showed a notable improvement in October 2025 compared to the previous year. The number of fatal crashes decreased by 44.4%, from 36 to 20, and the proportion of crashes resulting in no injuries increased from 75.5% to 76.8%. Correspondingly, crashes involving serious injuries (Type A) decreased from 131 to 100, and their share of all crashes fell from 1.4% to 1.0%.
Severity is per crash event (most severe injury). 20 fatal crash events resulted in 25 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2025-10-01 to 2025-10-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2025-10-01 to 2025-10-31 · Most severe injury per crash record
Road & Environmental Conditions
There was a substantial shift in the conditions under which crashes occurred. In October 2025, a much larger number of crashes happened during adverse weather, with 1,049 incidents reported in the rain, compared to only 125 in the prior year. This is reflected in road surface conditions, where crashes on wet roads increased from 220 to 1,269. The proportion of crashes occurring in daylight remained stable at approximately 70% for both periods.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2025-10-01 to 2025-10-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2025-10-01 to 2025-10-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2025-10-01 to 2025-10-31 · Road surface condition field
Vehicles & Demographics
The top five vehicle makes involved in crashes—Honda, Toyota, Ford, Nissan, and Chevrolet—remained the same across both periods with very similar incident counts, indicating stability in the makes of vehicles involved in collisions. Similarly, the age distribution of all persons involved in crashes was consistent year-over-year. For example, individuals in the 26-34 age group represented 16.2% of persons in the prior period and 16.7% in the current period, showing no significant demographic shift.
Top Vehicle Makes (18,158 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2025-10-01 to 2025-10-31 · Vehicle unit records
1,333 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (21,345 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2025-10-01 to 2025-10-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones was largely consistent year-over-year, but fatal outcomes within those zones shifted. Fatalities in low-speed zones (35 mph or less) dropped from 19 to 7, and fatalities in high-speed zones (65 mph or more) fell from 8 to 1. In contrast, fatalities in mid-range speed zones (40-55 mph) increased from 9 to 12, with the 45 mph zone accounting for 7 of those fatal crashes in the current period.
Fatal crashes by zone: 1 mph: 1 of 1,194 (0.084%) · 25 mph: 2 of 2,585 (0.077%) · 30 mph: 2 of 774 (0.258%) · 35 mph: 2 of 1,046 (0.191%) · 40 mph: 2 of 551 (0.363%) · 45 mph: 7 of 385 (1.818%) · 50 mph: 1 of 262 (0.382%) · 55 mph: 2 of 932 (0.215%) · 88 mph: 1 of 417 (0.24%)
Source: Connecticut Crash Data · Csv Open Data · 2025-10-01 to 2025-10-31 · 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: 2025-10-01 through 2025-10-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2025-10-01 through 2025-10-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 9,535
- Total persons involved: 22,958
- Total vehicles involved: 18,158
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: October 2025." Published August 20, 2026. Reporting period: 2025-10-01 to 2025-10-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/october-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: 2025-10-01 – 2025-10-31
Generated: August 20, 2026 · All rights reserved
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