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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
3,342 CRASHES IN
CONNECTICUT, CT
2021
In Middlesex County, total crashes increased from 2,930 in 2020 to 3,342 in 2021, a rise of 14.1%. While the number of crashes and total injuries (up 27.6% to 1,122) both increased, the number of fatalities saw a significant decrease, falling from 18 in the prior year to 10 in the current year.
3,342
▲ 14.1%was 2,930
Total Crash Events
10
▼ -44.4%was 18
Persons Killed
1,122
▲ 27.6%was 879
Persons Injured
293
▲ 10.6%was 265
Hit-and-Run Crashes
Note: "Persons Killed" (10) counts individual fatalities across all crash events. "Fatal" in the severity table below (10) 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
Crash data for Middlesex County shows a rising trend in the total number of collisions year-over-year. Total crashes increased by 14.1%, from 2,930 in 2020 to 3,342 in 2021. Similarly, the number of people injured in these incidents grew by 27.6% to 1,122, even as total fatalities declined.
293
Hit-and-Run Crashes — 2021
▲ 10.6% vs prior (265)
The total number of hit-and-run crashes in Middlesex County increased from 265 in 2020 to 293 in 2021. However, because the overall number of crashes grew at a faster pace, the hit-and-run rate as a percentage of all crashes slightly decreased. The rate fell from 9.0% in the prior year to 8.8% in the current year.
Vulnerable Road User Casualties
0
Pedestrians Killed
1
Cyclists Killed
9
Motorists Killed
30
Pedestrians Injured
13
Cyclists Injured
1,079
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 in Middlesex County remained broadly consistent year-over-year, with Fridays being the most common day for crashes in both 2021 (559 crashes) and 2020 (506 crashes). The peak hour for collisions shifted slightly later in the day, from the 3 PM hour in 2020 (269 crashes) to the 4 PM hour in 2021 (309 crashes). Overall, crash volumes increased on most days of the week, with the most significant daily increase occurring on Wednesdays, which saw 541 crashes compared to 429 in the prior year.
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 severity of those crashes showed a mixed trend. The number of fatal crashes decreased from 16 in 2020 to 10 in 2021, lowering the fatal crash rate from 0.5% to 0.3% of all collisions. However, the proportion of crashes involving any type of injury (Serious, Minor, or Possible) increased from 22.6% in 2020 to 25.1% in 2021. The share of crashes with no reported injuries fell from 76.9% to 74.6%.
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 across various environmental conditions showed little change between 2020 and 2021. In both years, the vast majority of collisions occurred during daylight hours (72.8% in 2021 vs. 71.3% in 2020) and on dry road surfaces (79.2% vs. 79.4%). Similarly, clear weather was reported in approximately 80% of crashes in both periods, indicating no significant shift toward crashes in adverse conditions.
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, with Toyota, Ford, and Honda being the top three in both 2021 and 2020. The total number of vehicles involved in crashes increased from 5,227 to 5,986. An analysis of persons involved shows that the 26-34 age group represented the largest share in both periods, accounting for 17.1% of individuals in 2021, up slightly from 16.0% in 2020.
Top Vehicle Makes (5,986 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records
328 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (7,324 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
Year-over-year data shows a notable increase in crashes occurring in 65 mph zones, which rose from 368 in 2020 to 500 in 2021. Collisions in 25 mph zones also increased from 507 to 610. Despite the rise in crashes in 65 mph zones, the number of fatal crashes in these areas decreased from 4 to 1. In 2021, the highest number of fatal crashes (5) occurred in 45 mph zones, a shift from 2020 where 65 mph zones had the most fatalities (4).
Fatal crashes by zone: 25 mph: 1 of 610 (0.164%) · 40 mph: 3 of 317 (0.946%) · 45 mph: 5 of 263 (1.901%) · 65 mph: 1 of 500 (0.2%)
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: 3,342
- Total persons involved: 7,716
- Total vehicles involved: 5,986
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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