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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · SEPTEMBER 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/september-2020-report
Monthly Traffic Safety Analysis
7,283 CRASHES IN
CONNECTICUT, CT
SEPTEMBER 2020
In September 2020, Connecticut recorded 7,283 total traffic crashes, a 20.9% decrease from the 9,204 crashes documented in September 2019. Despite this significant drop in overall collisions, the number of fatalities remained unchanged at 23 for both periods. The most notable year-over-year shift was the increase in the hit-and-run rate, which rose from 11.5% to 14.6% of all crashes.
7,283
▼ -20.9%was 9,204
Total Crash Events
23
Persons Killed
2,635
▼ -17.6%was 3,197
Persons Injured
1,066
▲ 0.9%was 1,057
Hit-and-Run Crashes
Note: "Persons Killed" (23) counts individual fatalities across all crash events. "Fatal" in the severity table below (22) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2020-09-01 to 2020-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic safety data indicates a downward trend in the total volume of crashes and injuries year-over-year. Total crashes fell by 20.9% from 9,204 to 7,283, and total injuries decreased by 17.6% from 3,197 to 2,635. However, the number of total fatalities held steady at 23 in both September 2019 and September 2020.
1,066
Hit-and-Run Crashes — September 2020
▲ 0.9% vs prior (1,057)
The absolute number of hit-and-run crashes was nearly stable, with 1,066 incidents in September 2020 compared to 1,057 in September 2019. However, due to the significant decrease in total crashes, the hit-and-run rate increased substantially year-over-year. This type of crash accounted for 14.6% of all collisions in the current period, up from 11.5% in the prior year.
Vulnerable Road User Casualties
4
Pedestrians Killed
1
Cyclists Killed
18
Motorists Killed
100
Pedestrians Injured
54
Cyclists Injured
2,481
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2020-09-01 to 2020-09-30 · 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. In September 2020, the peak day for crashes was Wednesday with 1,200 incidents, and the peak hour was 3 p.m. with 628 incidents. This contrasts with September 2019, when the peak day was Friday (1,486 crashes) and the peak hour was 4 p.m. (846 crashes), indicating a shift in peak collision times to earlier in the week and day.
Source: Connecticut Crash Data · Csv Open Data · 2020-09-01 to 2020-09-30 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2020-09-01 to 2020-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes decreased, the fatal crash rate increased from 0.23% in September 2019 to 0.30% in September 2020. The proportion of crashes resulting in a serious injury also saw an increase, rising from 1.2% to 1.6% of all incidents. Conversely, crashes categorized with 'Possible Injury' decreased as a share of the total, from 13.7% in the prior year to 12.6% in the current period.
Severity is per crash event (most severe injury). 22 fatal crash events resulted in 23 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2020-09-01 to 2020-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2020-09-01 to 2020-09-30 · Most severe injury per crash record
Road & Environmental Conditions
Year-over-year, the proportion of crashes occurring in adverse conditions saw a slight increase. Collisions in rainy weather rose from 5.3% of the total in September 2019 to 7.0% in September 2020. Similarly, crashes on wet road surfaces increased from 7.8% to 9.1% of all incidents. The share of crashes happening during daylight hours decreased from 75.4% to 71.5%, while those in dark but lighted conditions increased from 16.2% to 18.6%.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2020-09-01 to 2020-09-30 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2020-09-01 to 2020-09-30 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2020-09-01 to 2020-09-30 · Road surface condition field
Vehicles & Demographics
The top five vehicle makes involved in crashes—Honda, Toyota, Ford, Nissan, and Chevrolet—remained the same in both September 2019 and September 2020, though the count for each make decreased in line with the overall trend. The distribution of persons involved in crashes by age group remained largely consistent. The 26-34 age group was the largest cohort in both periods, accounting for 17.1% of persons in the prior year and 17.3% in the current year.
Top Vehicle Makes (13,700 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2020-09-01 to 2020-09-30 · Vehicle unit records
1,386 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (16,032 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2020-09-01 to 2020-09-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes decreased across all major speed zones compared to the previous year. However, the severity of crashes within some zones shifted. In the 25 mph zone, total crashes fell from 2,936 to 2,291, but the number of fatal crashes doubled from three to six. The fatal crash rate in the 65 mph zone also increased, rising from 0.61% in September 2019 to 0.98% in September 2020.
Fatal crashes by zone: 1 mph: 1 of 904 (0.111%) · 25 mph: 6 of 2,291 (0.262%) · 30 mph: 4 of 602 (0.664%) · 35 mph: 4 of 840 (0.476%) · 45 mph: 1 of 311 (0.322%) · 50 mph: 1 of 168 (0.595%) · 55 mph: 2 of 569 (0.351%) · 65 mph: 3 of 305 (0.984%)
Source: Connecticut Crash Data · Csv Open Data · 2020-09-01 to 2020-09-30 · 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: 2020-09-01 through 2020-09-30
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2020-09-01 through 2020-09-30 (30 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 7,283
- Total persons involved: 17,358
- Total vehicles involved: 13,700
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: September 2020." Published August 20, 2026. Reporting period: 2020-09-01 to 2020-09-30. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/september-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: 2020-09-01 – 2020-09-30
Generated: August 20, 2026 · All rights reserved
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