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YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · NOVEMBER 2023
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-2023-report
Monthly Traffic Safety Analysis
8,651 CRASHES IN
CONNECTICUT, CT
NOVEMBER 2023
In November 2023, Connecticut recorded 8,651 vehicle crashes, a 3.8% decrease from the 8,994 crashes reported in November 2022. The most significant year-over-year change was a 61.9% reduction in traffic fatalities, which fell from 42 in the prior period to 16 in the current period. Total injuries also saw a decline, dropping from 2,883 to 2,641.
8,651
▼ -3.8%was 8,994
Total Crash Events
16
▼ -61.9%was 42
Persons Killed
2,641
▼ -8.4%was 2,883
Persons Injured
994
▼ -7.5%was 1,075
Hit-and-Run Crashes
Note: "Persons Killed" (16) counts individual fatalities across all crash events. "Fatal" in the severity table below (14) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2023-11-01 to 2023-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety trends improved in November 2023 compared to the same month in 2022. Total crashes decreased by 3.8%, from 8,994 to 8,651. This downward trend was also reflected in crash outcomes, with total injuries falling by 8.4% and total fatalities declining significantly by 61.9%.
994
Hit-and-Run Crashes — November 2023
▼ -7.5% vs prior (1,075)
The number of hit-and-run incidents decreased from November 2022 to November 2023. The total count of hit-and-run crashes fell from 1,075 to 994. Correspondingly, the hit-and-run rate, which measures the percentage of all crashes that were hit-and-runs, saw a slight decline from 12.0% to 11.5%, indicating a small downward trend for this type of crash.
Vulnerable Road User Casualties
4
Pedestrians Killed
0
Cyclists Killed
12
Motorists Killed
105
Pedestrians Injured
20
Cyclists Injured
2,516
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2023-11-01 to 2023-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed some shifts between November 2022 and November 2023. The peak day for crashes moved from Tuesday (1,565 crashes) in the prior period to Wednesday (1,694 crashes) in the current period. The peak hour for collisions remained consistent, occurring during the 5 p.m. hour in both periods, with a slight increase in volume from 927 to 937 crashes. Crashes on Tuesdays decreased from 1,565 to 1,269, while Wednesdays saw an increase from 1,555 to 1,694.
Source: Connecticut Crash Data · Csv Open Data · 2023-11-01 to 2023-11-30 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2023-11-01 to 2023-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity decreased in November 2023 compared to the previous year. The fatal crash rate fell from 0.43% to 0.16%, with fatal crashes accounting for 0.2% of all incidents, down from 0.4% in November 2022. The proportion of crashes resulting in any form of injury (serious, minor, or possible) also declined slightly, from 23.4% of all crashes in the prior period to 22.2% in the current period. Consequently, crashes resulting in no injury comprised 77.7% of the total, up from 76.2%.
Severity is per crash event (most severe injury). 14 fatal crash events resulted in 16 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2023-11-01 to 2023-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2023-11-01 to 2023-11-30 · Most severe injury per crash record
Road & Environmental Conditions
The majority of crashes in both periods occurred in clear weather and on dry roads. However, there was a notable year-over-year shift in the prevalence of adverse weather-related incidents. Crashes during rain decreased from 10.9% of all crashes in November 2022 to 5.1% in November 2023. Similarly, collisions on wet road surfaces fell from 14.7% of the total to 8.4%. The distribution of crashes by lighting conditions remained relatively stable, with daylight crashes accounting for 57.6% of the total in the current period compared to 55.9% in the prior period.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2023-11-01 to 2023-11-30 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2023-11-01 to 2023-11-30 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2023-11-01 to 2023-11-30 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes remained consistent year-over-year. In both November 2022 and 2023, Honda, Toyota, and Ford were the top three makes, with their involvement counts showing only minor fluctuations. The age demographics of individuals involved in crashes were also stable; the 26-34 age group was the most frequently involved in both periods, followed by the 35-44 age group, with no significant shifts in their proportional representation.
Top Vehicle Makes (16,556 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2023-11-01 to 2023-11-30 · Vehicle unit records
1,327 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (19,470 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2023-11-01 to 2023-11-30 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across posted speed limit zones was similar in November 2023 compared to the prior year, with the 25 mph zone accounting for the highest volume of incidents in both periods (2,399 and 2,512, respectively). However, there was a substantial decrease in fatalities within specific speed zones. Fatal crashes in the 25 mph zone fell from 10 to 3, and zones with a speed limit of 65 mph recorded zero fatalities, down from 5 in the prior period. Crashes in zones with posted limits of 40 mph also saw fatalities drop from 6 to 2.
Fatal crashes by zone: 1 mph: 1 of 1,119 (0.089%) · 25 mph: 3 of 2,399 (0.125%) · 30 mph: 3 of 682 (0.44%) · 35 mph: 2 of 1,035 (0.193%) · 40 mph: 2 of 503 (0.398%) · 45 mph: 1 of 324 (0.309%) · 50 mph: 1 of 238 (0.42%) · 55 mph: 1 of 870 (0.115%)
Source: Connecticut Crash Data · Csv Open Data · 2023-11-01 to 2023-11-30 · 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: 2023-11-01 through 2023-11-30
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2023-11-01 through 2023-11-30 (30 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 8,651
- Total persons involved: 20,988
- Total vehicles involved: 16,556
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 2023." Published August 20, 2026. Reporting period: 2023-11-01 to 2023-11-30. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/november-2023-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: 2023-11-01 – 2023-11-30
Generated: August 20, 2026 · All rights reserved
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