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ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · FEBRUARY 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/february-2020-report
Monthly Traffic Safety Analysis
7,723 CRASHES IN
CONNECTICUT, CT
FEBRUARY 2020
In February 2020, Connecticut recorded 7,723 motor vehicle crashes, an 8.7% decrease from the 8,459 crashes reported in February 2019. Despite the overall reduction in collisions, the number of fatalities increased significantly, rising from 13 in the prior year to 22 in the current period.
7,723
▼ -8.7%was 8,459
Total Crash Events
22
▲ 69.2%was 13
Persons Killed
2,562
▲ 2.8%was 2,493
Persons Injured
977
▼ -0.1%was 978
Hit-and-Run Crashes
Note: "Persons Killed" (22) counts individual fatalities across all crash events. "Fatal" in the severity table below (20) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2020-02-01 to 2020-02-29 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Statewide crash data indicates a downward trend in the total volume of collisions, which fell by 8.7% from February 2019 to February 2020. However, the severity of these incidents worsened year-over-year. Total injuries increased by 2.8% from 2,493 to 2,562, and total fatalities rose by 69.2% from 13 to 22.
977
Hit-and-Run Crashes — February 2020
▼ -0.1% vs prior (978)
The absolute number of hit-and-run crashes remained nearly unchanged, with 977 incidents in February 2020 compared to 978 in February 2019. However, due to the overall decrease in total collisions statewide, the hit-and-run rate increased. These incidents accounted for 12.7% of all crashes in the current period, up from 11.6% in the prior year.
Vulnerable Road User Casualties
7
Pedestrians Killed
0
Cyclists Killed
15
Motorists Killed
111
Pedestrians Injured
11
Cyclists Injured
2,440
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2020-02-01 to 2020-02-29 · 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 year-over-year. The peak day for crashes moved from Tuesday (1,440 crashes) in the prior period to Friday (1,429 crashes) in the current period. Similarly, the peak hour for collisions shifted slightly earlier, from 4 p.m. (722 crashes) in February 2019 to 3 p.m. (647 crashes) in February 2020.
Source: Connecticut Crash Data · Csv Open Data · 2020-02-01 to 2020-02-29 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2020-02-01 to 2020-02-29 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes decreased, the severity of crashes increased from the prior year. The number of fatal crashes nearly doubled, rising from 11 to 20, and the fatal crash rate increased from 0.1% to 0.3% of all crashes. The proportion of crashes resulting in minor injuries also grew, from 7.9% in the prior period to 9.8% in the current period, while no-injury crashes decreased as a percentage of the total from 78.3% to 76.0%.
Severity is per crash event (most severe injury). 20 fatal crash events resulted in 22 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2020-02-01 to 2020-02-29 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2020-02-01 to 2020-02-29 · Most severe injury per crash record
Road & Environmental Conditions
Crash conditions varied significantly between the two periods, largely reflecting different weather patterns. In February 2020, 15.4% of crashes occurred during rain and 23.8% on wet roads, a substantial increase from 4.7% and 13.2% respectively in the prior year. Conversely, crashes in snow conditions dropped from 8.7% of the total in 2019 to just 0.5% in 2020. The proportion of crashes in daylight decreased from 64.6% to 61.3%, while those in dark-lighted conditions increased from 23.5% to 27.1%.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2020-02-01 to 2020-02-29 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2020-02-01 to 2020-02-29 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2020-02-01 to 2020-02-29 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in collisions remained consistent year-over-year, with Honda, Toyota, and Ford leading in both February 2019 and February 2020. An analysis of persons involved shows a stable demographic distribution across most age groups. However, the proportion of individuals aged 65 and older involved in crashes saw a slight increase, rising from 8.5% of all persons in the prior period to 9.4% in the current period.
Top Vehicle Makes (14,653 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2020-02-01 to 2020-02-29 · Vehicle unit records
1,277 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (17,639 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2020-02-01 to 2020-02-29 · Person-level records linked to crash events
Speed Limit Zones
Year-over-year data shows a decrease in crashes within higher speed zones, with collisions in 65 mph zones falling from 515 to 349. Despite this trend, the number of fatal crashes increased in mid-range speed zones. Zones with posted speed limits of 40 mph and 45 mph, which had a combined one fatal crash in the prior period, accounted for a total of eight fatal crashes in February 2020.
Fatal crashes by zone: 1 mph: 1 of 968 (0.103%) · 25 mph: 4 of 2,486 (0.161%) · 30 mph: 1 of 606 (0.165%) · 35 mph: 2 of 957 (0.209%) · 40 mph: 4 of 454 (0.881%) · 45 mph: 4 of 267 (1.498%) · 55 mph: 1 of 606 (0.165%) · 65 mph: 3 of 349 (0.86%)
Source: Connecticut Crash Data · Csv Open Data · 2020-02-01 to 2020-02-29 · 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: 2020-02-01 through 2020-02-29
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2020-02-01 through 2020-02-29 (29 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 7,723
- Total persons involved: 18,848
- Total vehicles involved: 14,653
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: February 2020." Published August 20, 2026. Reporting period: 2020-02-01 to 2020-02-29. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/february-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: 2020-02-01 – 2020-02-29
Generated: August 20, 2026 · All rights reserved
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