If you're a data point in this report, call us.
We'll evaluate whether you have a case. Free, and no pressure.
ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · NOVEMBER 2024
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/november-2024-report
Monthly Traffic Safety Analysis
9,154 CRASHES IN
CONNECTICUT, CT
NOVEMBER 2024
In November 2024, Connecticut recorded 9,154 traffic crashes, a 5.8% increase from the 8,651 crashes reported in November 2023. The total number of injuries rose by 6.0% from 2,641 to 2,799. The most notable year-over-year shift was a 37.5% increase in traffic fatalities, which climbed from 16 to 22.
9,154
▲ 5.8%was 8,651
Total Crash Events
22
▲ 37.5%was 16
Persons Killed
2,799
▲ 6.0%was 2,641
Persons Injured
1,154
▲ 16.1%was 994
Hit-and-Run Crashes
Note: "Persons Killed" (22) 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 · 2024-11-01 to 2024-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety trends worsened in November 2024 compared to the same month in the prior year. Total crashes increased by 5.8% from 8,651 to 9,154. This upward trend included a 6.0% rise in persons injured and a significant 37.5% increase in persons killed in collisions.
1,154
Hit-and-Run Crashes — November 2024
▲ 16.1% vs prior (994)
Hit-and-run crashes trended upward in November 2024. The total number of hit-and-run incidents increased by 16.1%, from 994 in the prior year to 1,154 in the current period. The hit-and-run rate, representing the proportion of all crashes that were hit-and-runs, also increased from 11.5% to 12.6%.
Vulnerable Road User Casualties
7
Pedestrians Killed
0
Cyclists Killed
15
Motorists Killed
127
Pedestrians Injured
34
Cyclists Injured
2,638
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2024-11-01 to 2024-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted year-over-year. The peak day for collisions moved from Wednesday (1,694 crashes) in November 2023 to Friday (1,771 crashes) in November 2024. The peak hour for crashes remained the 5 PM hour in both periods, though the number of incidents during this hour increased from 937 to 1,011.
Source: Connecticut Crash Data · Csv Open Data · 2024-11-01 to 2024-11-30 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2024-11-01 to 2024-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes increased in November 2024 compared to the prior year. The number of fatal crashes rose from 14 to 20, increasing the fatal crash rate from 0.16% to 0.22% of all collisions. The proportion of crashes involving any type of injury (Serious, Minor, or Possible) also grew slightly, from 22.1% in November 2023 to 22.9% in the current period.
Severity is per crash event (most severe injury). 20 fatal crash events resulted in 22 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2024-11-01 to 2024-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2024-11-01 to 2024-11-30 · Most severe injury per crash record
Road & Environmental Conditions
A higher proportion of crashes occurred in adverse conditions in November 2024 compared to the previous year. The number of crashes during rain nearly doubled from 441 to 873, and collisions on wet road surfaces increased from 725 to 1,276. Consequently, the share of crashes on wet roads rose from 8.4% to 13.9% of the monthly total. The distribution of crashes by lighting condition remained stable between the two periods.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2024-11-01 to 2024-11-30 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2024-11-01 to 2024-11-30 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2024-11-01 to 2024-11-30 · Road surface condition field
Vehicles & Demographics
The top five vehicle makes involved in collisions—Honda, Toyota, Ford, Nissan, and Chevrolet—were the same in both November 2023 and November 2024, with counts increasing in line with the overall rise in crashes. The age demographics of persons involved in crashes also remained consistent, with the 26-34 age group being the largest cohort in both periods, increasing from 3,481 individuals to 3,641.
Top Vehicle Makes (17,313 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2024-11-01 to 2024-11-30 · Vehicle unit records
1,369 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (20,318 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2024-11-01 to 2024-11-30 · Person-level records linked to crash events
Speed Limit Zones
While the overall distribution of crashes across speed zones was similar year-over-year, with 25 mph zones seeing the most incidents in both periods, the locations of fatal crashes shifted. In November 2024, 5 fatal crashes occurred in 65 mph zones, a zone that had zero fatal crashes in November 2023. In contrast, fatal crashes in 30 mph zones decreased from 3 to 1.
Fatal crashes by zone: 25 mph: 4 of 2,504 (0.16%) · 30 mph: 1 of 812 (0.123%) · 35 mph: 4 of 1,067 (0.375%) · 40 mph: 4 of 545 (0.734%) · 65 mph: 5 of 623 (0.803%) · 88 mph: 1 of 433 (0.231%) · 99 mph: 1 of 23 (4.348%)
Source: Connecticut Crash Data · Csv Open Data · 2024-11-01 to 2024-11-30 · 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: 2024-11-01 through 2024-11-30
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2024-11-01 through 2024-11-30 (30 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 9,154
- Total persons involved: 21,970
- Total vehicles involved: 17,313
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: November 2024." Published August 20, 2026. Reporting period: 2024-11-01 to 2024-11-30. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/november-2024-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: 2024-11-01 – 2024-11-30
Generated: August 20, 2026 · All rights reserved
The data is step one. Get a Connecticut attorney on the line.
Call our intake team. We connect you to a vetted Connecticut personal injury attorney who calls you back within minutes. No phone tag. No voicemails.
Always free for accident victims.