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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · NOVEMBER 2020
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-2020-report
Monthly Traffic Safety Analysis
7,478 CRASHES IN
CONNECTICUT, CT
NOVEMBER 2020
In November 2020, Connecticut recorded 7,478 total vehicle crashes, a 23.2% decrease from the 9,738 crashes reported in November 2019. Despite this significant drop in overall collisions, the number of fatalities more than doubled, rising from 16 to 35 year-over-year. This sharp increase in fatalities, coupled with a higher fatal crash rate, represents the most notable shift in the data.
7,478
▼ -23.2%was 9,738
Total Crash Events
35
▲ 118.8%was 16
Persons Killed
2,601
▼ -15.7%was 3,087
Persons Injured
1,065
▼ -6.7%was 1,142
Hit-and-Run Crashes
Note: "Persons Killed" (35) counts individual fatalities across all crash events. "Fatal" in the severity table below (33) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2020-11-01 to 2020-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend shows a significant year-over-year decrease in the total number of crashes and injuries. Total crashes fell by 23.2% from 9,738 to 7,478, and injuries declined by 15.7% from 3,087 to 2,601. In stark contrast, fatalities increased by 118.8%, from 16 in November 2019 to 35 in November 2020, indicating that collisions became substantially more lethal.
1,065
Hit-and-Run Crashes — November 2020
▼ -6.7% vs prior (1,142)
The total number of hit-and-run crashes saw a slight decrease from 1,142 in November 2019 to 1,065 in November 2020. However, due to the larger overall drop in total crashes, the hit-and-run rate trended upward. Hit-and-runs constituted 14.2% of all crashes in the current period, an increase from the 11.7% rate recorded in the prior year.
Vulnerable Road User Casualties
9
Pedestrians Killed
1
Cyclists Killed
25
Motorists Killed
111
Pedestrians Injured
22
Cyclists Injured
2,468
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2020-11-01 to 2020-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak hour for crashes remained consistent at the 5 p.m. hour for both November 2019 and November 2020, although the volume of crashes during this hour decreased from 1,129 to 766. A notable shift occurred in the peak day of the week for crashes, moving from Friday (1,993 crashes) in the prior year to Monday (1,310 crashes) in the current period. Overall crash counts were lower across nearly all days and hours in November 2020 compared to the previous year.
Source: Connecticut Crash Data · Csv Open Data · 2020-11-01 to 2020-11-30 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2020-11-01 to 2020-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity worsened significantly in November 2020 compared to the prior year. The number of fatal crashes more than doubled from 16 to 33, and the fatal crash rate increased from 0.16% to 0.44%. The count of serious injury crashes also rose from 74 to 111, with their proportion of total crashes increasing from 0.8% to 1.5%. Consequently, the share of crashes with no reported injuries fell from 76.8% to 74.0%.
Severity is per crash event (most severe injury). 33 fatal crash events resulted in 35 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2020-11-01 to 2020-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2020-11-01 to 2020-11-30 · Most severe injury per crash record
Road & Environmental Conditions
In November 2020, a greater proportion of crashes occurred in adverse conditions compared to the same month in 2019. The share of crashes on wet road surfaces increased from 14.4% to 21.2% year-over-year. Similarly, collisions during rainy weather constituted 15.1% of all crashes, up from 9.5% in the prior period. The percentage of crashes occurring in daylight decreased slightly from 56.1% to 54.1%.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2020-11-01 to 2020-11-30 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2020-11-01 to 2020-11-30 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2020-11-01 to 2020-11-30 · Road surface condition field
Vehicles & Demographics
The top five vehicle makes involved in crashes—Honda, Toyota, Nissan, Ford, and Chevrolet—remained the same in November 2020 as in November 2019, though the counts for each make decreased in line with the overall reduction in crashes. The age distribution of persons involved in crashes was also largely consistent, with the 26-34 age group being the most represented in both periods. There was a minor proportional increase in the involvement of the 55-64 and 65+ age groups in the current period.
Top Vehicle Makes (13,842 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2020-11-01 to 2020-11-30 · Vehicle unit records
1,365 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (15,987 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2020-11-01 to 2020-11-30 · Person-level records linked to crash events
Speed Limit Zones
While total crashes decreased across most speed zones, fatal crashes saw a notable shift toward higher-speed roads. In November 2020, crashes in 55 mph zones resulted in 9 fatalities, a sharp rise from 2 fatalities in November 2019, even as total crashes in that zone dropped from 909 to 609. Fatalities in 25 mph zones also increased from 3 to 5, despite a decrease in total crashes in that zone from 2,927 to 2,275.
Fatal crashes by zone: 1 mph: 1 of 861 (0.116%) · 25 mph: 5 of 2,275 (0.22%) · 30 mph: 5 of 639 (0.782%) · 35 mph: 3 of 927 (0.324%) · 40 mph: 3 of 447 (0.671%) · 45 mph: 3 of 279 (1.075%) · 55 mph: 9 of 609 (1.478%) · 65 mph: 3 of 414 (0.725%)
Source: Connecticut Crash Data · Csv Open Data · 2020-11-01 to 2020-11-30 · 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: 2020-11-01 through 2020-11-30
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2020-11-01 through 2020-11-30 (30 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 7,478
- Total persons involved: 17,351
- Total vehicles involved: 13,842
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 2020." Published August 20, 2026. Reporting period: 2020-11-01 to 2020-11-30. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/november-2020-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: 2020-11-01 – 2020-11-30
Generated: August 20, 2026 · All rights reserved
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