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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
30,014 CRASHES IN
CONNECTICUT, CT
2021
In 2021, Fairfield County recorded 30,014 total vehicle crashes, a 28.7% increase from the 23,323 crashes reported in 2020. Despite this significant rise in overall collisions and a 23.7% increase in injuries, the number of fatalities decreased from 58 in the prior period to 39 in the current period.
30,014
▲ 28.7%was 23,323
Total Crash Events
39
▼ -32.8%was 58
Persons Killed
8,906
▲ 23.7%was 7,199
Persons Injured
3,575
▲ 24.1%was 2,881
Hit-and-Run Crashes
Note: "Persons Killed" (39) counts individual fatalities across all crash events. "Fatal" in the severity table below (38) 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
Traffic crash volume in Fairfield County showed a significant upward trend year-over-year. Total crashes increased by 28.7% from 23,323 in 2020 to 30,014 in 2021. Similarly, the number of people injured in these incidents rose by 23.7%, from 7,199 to 8,906.
3,575
Hit-and-Run Crashes — 2021
▲ 24.1% vs prior (2,881)
The total number of hit-and-run crashes increased from 2,881 in 2020 to 3,575 in 2021, following the overall trend of rising crash volumes. However, as a proportion of all crashes, hit-and-runs became slightly less common. The hit-and-run rate decreased from 12.4% of all crashes in the prior year to 11.9% in the current year.
Vulnerable Road User Casualties
4
Pedestrians Killed
0
Cyclists Killed
35
Motorists Killed
335
Pedestrians Injured
96
Cyclists Injured
8,475
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. While Friday remained the peak day for crashes in both 2020 (3,966 crashes) and 2021 (5,179 crashes), the peak hour moved earlier. In 2021, the highest number of crashes occurred at 3 PM (2,452 crashes), a shift from the 5 PM peak observed in the prior year (1,930 crashes).
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 rose, the severity profile showed a notable decrease in fatal outcomes. The fatal crash rate fell from 0.24 per 100 crashes in 2020 to 0.13 in 2021, with total fatalities dropping from 58 to 39. The proportion of crashes resulting in serious or possible injuries remained stable at 1.1% and 11.7% respectively, though the absolute number of these incidents increased with the overall rise in crash volume.
Severity is per crash event (most severe injury). 38 fatal crash events resulted in 39 persons killed.
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 majority of crashes in both periods occurred under ideal conditions: in daylight, on dry roads, and in clear weather. In 2021, 83.1% of crashes happened in clear weather, a slight proportional increase from 81.6% in 2020. Similarly, the proportion of crashes on dry surfaces rose to 83.4% from 81.7% in the prior year. There were no significant shifts indicating that adverse weather or lighting conditions played a larger role in crashes year-over-year.
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
The makes of vehicles involved in crashes remained consistent year-over-year, with Honda, Toyota, and Ford being the top three in both periods. The number of vehicles from these makes involved in crashes increased, consistent with the overall rise in collisions, but their rank order did not change. The age distribution of all persons involved in crashes also showed no significant shifts, with all age groups representing a similar proportion of the total in 2021 as they did in 2020.
Top Vehicle Makes (58,014 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records
4,719 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (66,309 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
Crashes increased across most reported speed zones, with notable growth in zones posted at 25 mph (from 8,702 to 10,375 crashes) and 55 mph (from 3,255 to 5,279 crashes). Despite the rise in crash volume in these zones, the number of associated fatal crashes decreased. In the 55 mph zone, fatalities were halved from 20 in 2020 to 10 in 2021, and in the 25 mph zone, they fell from 15 to 9.
Fatal crashes by zone: 20 mph: 1 of 173 (0.578%) · 25 mph: 9 of 10,375 (0.087%) · 30 mph: 6 of 2,226 (0.27%) · 35 mph: 7 of 2,080 (0.337%) · 40 mph: 1 of 975 (0.103%) · 45 mph: 1 of 211 (0.474%) · 50 mph: 2 of 193 (1.036%) · 55 mph: 10 of 5,279 (0.189%) · 88 mph: 1 of 1,796 (0.056%)
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: August 20, 2026
Data Coverage
- Reporting period: 2021-01-01 through 2021-12-31 (365 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 30,014
- Total persons involved: 71,199
- Total vehicles involved: 58,014
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 August 20, 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: August 20, 2026 · All rights reserved
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