ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · 2021
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/2021-annual-report
Yearly Traffic Safety Analysis
3,755 CRASHES IN
CONNECTICUT, CT
2021
In Litchfield County, traffic crashes increased from 3,056 in 2020 to 3,755 in 2021, representing a 22.9% year-over-year rise. This increase in collisions was accompanied by a 15.2% rise in injuries, from 999 to 1,151. The most notable shift was the overall surge in crash volume, even as the number of fatalities remained nearly stable, decreasing by one from 20 to 19.
3,755
▲ 22.9%was 3,056
Total Crash Events
19
▼ -5.0%was 20
Persons Killed
1,151
▲ 15.2%was 999
Persons Injured
263
▲ 9.6%was 240
Hit-and-Run Crashes
Note: "Persons Killed" (19) counts individual fatalities across all crash events. "Fatal" in the severity table below (19) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend in Litchfield County shows a significant increase in traffic incidents year-over-year. Total crashes rose by 22.9%, from 3,056 in 2020 to 3,755 in 2021. Correspondingly, the number of people injured increased by 15.2% to 1,151, while fatalities saw a slight decrease from 20 to 19.
263
Hit-and-Run Crashes — 2021
▲ 9.6% vs prior (240)
The number of hit-and-run incidents increased from 240 in 2020 to 263 in 2021. However, due to the larger overall increase in total crashes, the hit-and-run rate as a percentage of all crashes decreased. This type of incident accounted for 7.0% of all crashes in 2021, down from 7.9% in the prior year.
Vulnerable Road User Casualties
1
Pedestrians Killed
1
Cyclists Killed
17
Motorists Killed
25
Pedestrians Injured
4
Cyclists Injured
1,122
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-12-31 · 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 between the two periods. In 2021, Friday was the peak day for crashes with 611 incidents, a change from 2020 when Saturday was the peak day with 515 crashes. The peak hour also shifted one hour later, from 2 p.m. in 2020 (269 crashes) to 3 p.m. in 2021 (330 crashes), indicating the afternoon commute remains the most frequent time for collisions.
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes increased, the fatal crash rate decreased from 0.62% in 2020 to 0.51% in 2021, with total fatalities declining from 20 to 19. The proportion of crashes resulting in any level of injury also saw a slight decline, from 24.8% of all crashes in 2020 to 23.4% in 2021. However, the absolute number of minor injury crashes grew from 354 to 467, consistent with the overall increase in crash volume.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-12-31 · Most severe injury per crash record
Road & Environmental Conditions
The distribution of crashes by environmental conditions remained largely stable year-over-year. In both 2021 and 2020, crashes in daylight and on dry road surfaces were the most common scenarios, with their proportions changing by less than two percentage points. Crashes during clear weather accounted for 76.4% of incidents in 2021, slightly down from 77.9% in 2020, while the proportion of crashes in snow conditions increased from 3.4% to 5.0%.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-12-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-12-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-12-31 · Road surface condition field
Vehicles & Demographics
Ford, Honda, and Chevrolet were consistently among the top makes of vehicles involved in crashes in both years. A notable shift occurred with Subaru, which moved from the fifth most frequent make in 2020 (321 vehicles) to the second in 2021 (566 vehicles). The proportional involvement of different age groups in crashes remained steady, with the 26-34 age group constituting the largest cohort in both periods, accounting for 15.7% of persons in 2020 and 16.0% in 2021.
Top Vehicle Makes (6,282 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records
294 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (7,472 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-12-31 · Person-level records linked to crash events
Speed Limit Zones
The increase in crashes was observed across multiple speed zones, with notable rises in 25 mph zones (from 715 to 911 crashes) and 45 mph zones (from 266 to 375 crashes). In 2021, the highest number of fatal crashes (7) occurred in 45 mph zones, where the fatal crash rate increased to 1.87% from 1.13% in the prior year. In contrast, 55 mph zones, which had a fatal crash rate of 8% in 2020, recorded no fatalities in 2021.
Fatal crashes by zone: 25 mph: 4 of 911 (0.439%) · 35 mph: 2 of 575 (0.348%) · 40 mph: 4 of 386 (1.036%) · 45 mph: 7 of 375 (1.867%) · 65 mph: 2 of 202 (0.99%)
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-12-31 · 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: 2021-01-01 through 2021-12-31
- Report generated: September 10, 2026
Data Coverage
- Reporting period: 2021-01-01 through 2021-12-31 (365 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 3,755
- Total persons involved: 8,171
- Total vehicles involved: 6,282
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: 2021." Published September 10, 2026. Reporting period: 2021-01-01 to 2021-12-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/2021-annual-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: 2021-01-01 – 2021-12-31
Generated: September 10, 2026 · All rights reserved