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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · JANUARY 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/january-2021-report
Monthly Traffic Safety Analysis
6,745 CRASHES IN
CONNECTICUT, CT
JANUARY 2021
In January 2021, Connecticut recorded 6,745 total crashes, a 24.4% decrease from the 8,921 crashes reported in January 2020. This significant year-over-year reduction in crash volume was the most notable shift in the data. Correspondingly, total injuries fell from 2,702 to 2,094, and fatalities decreased from 23 to 19.
6,745
▼ -24.4%was 8,921
Total Crash Events
19
▼ -17.4%was 23
Persons Killed
2,094
▼ -22.5%was 2,702
Persons Injured
1,014
▼ -9.5%was 1,120
Hit-and-Run Crashes
Note: "Persons Killed" (19) counts individual fatalities across all crash events. "Fatal" in the severity table below (18) 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 2021-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic safety metrics showed a significant downward trend in January 2021 compared to the same month in the prior year. Total crashes fell by 24.4%, from 8,921 to 6,745. This decline was also reflected in casualties, with total injuries decreasing by 22.5% from 2,702 to 2,094 and fatalities dropping from 23 to 19.
1,014
Hit-and-Run Crashes — January 2021
▼ -9.5% vs prior (1,120)
The total number of hit-and-run crashes saw a slight decrease from 1,120 in January 2020 to 1,014 in January 2021. However, as a proportion of all crashes, hit-and-runs became more frequent. The hit-and-run rate increased from 12.6% in the prior year to 15.0% in the current period, indicating that a larger percentage of total crashes involved a driver leaving the scene.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
19
Motorists Killed
99
Pedestrians Injured
11
Cyclists Injured
1,984
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-01-31 · 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 between the two periods. While the peak hour for crashes remained 5 p.m. in both January 2021 (631 crashes) and January 2020 (954 crashes), the peak day changed from Friday (1,644 crashes) in the prior year to Tuesday (1,166 crashes) in the current year. Crash volumes were lower across all days of the week and most hours of the day compared to the previous year.
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-01-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the total number of crashes decreased, the severity profile of those crashes shifted. The proportion of fatal crashes remained stable at 0.3% in both January 2021 and January 2020. However, the share of crashes resulting in serious injuries increased from 0.8% to 1.2% year-over-year. Similarly, minor injury crashes grew from 8.5% to 9.8% of the total, while the proportion of crashes with no injuries decreased from 77.7% to 76.9%.
Severity is per crash event (most severe injury). 18 fatal crash events resulted in 19 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-01-31 · Most severe injury per crash record
Road & Environmental Conditions
The distribution of crashes by environmental conditions remained broadly similar year-over-year. In both January 2021 and January 2020, approximately 80% of crashes occurred in clear weather and on dry roads. Crashes in daylight accounted for 54.8% of the total in the current period, a slight decrease from 57.6% in the prior period. The proportion of crashes occurring in snowy weather increased from 7.2% to 10.2%, with a corresponding increase in crashes on snow-covered road surfaces.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-01-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-01-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-01-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes showed a consistent pattern, with Honda, Toyota, and Ford being the top three most frequently involved makes in both January 2021 and January 2020. The age distribution of persons involved in crashes also remained stable. The 26-34 age group constituted the largest share of individuals in both periods, accounting for 18.2% of persons in the current year compared to 17.0% in the prior year.
Top Vehicle Makes (12,386 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-01-31 · Vehicle unit records
1,210 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (14,097 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes decreased across all posted speed limit zones in January 2021 compared to the prior year. The 25 mph zone remained the location with the highest number of crashes, recording 2,092 incidents, down from 2,891 in January 2020. Fatalities in these 25 mph zones also decreased from 7 to 3. While overall crash counts were lower, the fatal crash rate for collisions in 45 mph zones saw a slight increase from 1.42% to 1.67% year-over-year.
Fatal crashes by zone: 25 mph: 3 of 2,092 (0.143%) · 30 mph: 4 of 607 (0.659%) · 35 mph: 2 of 844 (0.237%) · 45 mph: 4 of 240 (1.667%) · 50 mph: 2 of 160 (1.25%) · 55 mph: 1 of 463 (0.216%) · 65 mph: 1 of 319 (0.313%) · 88 mph: 1 of 497 (0.201%)
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-01-31 · 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 2021-01-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2021-01-01 through 2021-01-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 6,745
- Total persons involved: 15,329
- Total vehicles involved: 12,386
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: January 2021." Published August 20, 2026. Reporting period: 2021-01-01 to 2021-01-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/january-2021-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 – 2021-01-31
Generated: August 20, 2026 · All rights reserved
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