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ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · JULY 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/july-2020-report
Monthly Traffic Safety Analysis
6,977 CRASHES IN
CONNECTICUT, CT
JULY 2020
In July 2020, there were 6,977 total crashes recorded statewide, representing a 25.0% decrease from the 9,299 crashes in July 2019. This overall decline in crash volume was the most significant year-over-year shift. While total crashes, injuries (down 19.0%), and fatalities (down 13.8%) all decreased, the rate of crashes that were fatal or involved a hit-and-run both increased.
6,977
▼ -25.0%was 9,299
Total Crash Events
25
▼ -13.8%was 29
Persons Killed
2,670
▼ -19.0%was 3,296
Persons Injured
1,004
▼ -3.3%was 1,038
Hit-and-Run Crashes
Note: "Persons Killed" (25) counts individual fatalities across all crash events. "Fatal" in the severity table below (26) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2020-07-01 to 2020-07-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic safety metrics showed a downward trend in volume year-over-year. Total crashes fell by 25.0%, from 9,299 in July 2019 to 6,977 in July 2020. Correspondingly, total injuries decreased by 19.0% from 3,296 to 2,670, and total fatalities declined from 29 to 25.
1,004
Hit-and-Run Crashes — July 2020
▼ -3.3% vs prior (1,038)
While the absolute number of hit-and-run crashes decreased slightly from 1,038 to 1,004 year-over-year, the hit-and-run rate trended upward. In July 2020, hit-and-runs accounted for 14.4% of all crashes, a significant increase from the 11.2% rate recorded in July 2019. This indicates that the proportion of crashes where a driver left the scene grew despite the overall decline in collisions.
Vulnerable Road User Casualties
6
Pedestrians Killed
0
Cyclists Killed
19
Motorists Killed
0
Other Killed
57
Pedestrians Injured
59
Cyclists Injured
2,552
Motorists Injured
2
Other Injured
Source: Connecticut Crash Data · Csv Open Data · 2020-07-01 to 2020-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Wednesday (1,599 crashes) in July 2019 to Friday (1,268 crashes) in July 2020. The peak hour for collisions remained 4 p.m. in both periods. However, the number of crashes during that hour decreased from 839 in the prior year to 578 in the current period, reflecting the overall reduction in crash volume.
Source: Connecticut Crash Data · Csv Open Data · 2020-07-01 to 2020-07-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2020-07-01 to 2020-07-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Although the number of fatal crashes fell from 29 to 26, the fatal crash rate per 100 crashes increased from 0.31 to 0.37 year-over-year. The proportion of crashes resulting in any injury also grew, rising from 25.4% of all crashes in July 2019 to 27.5% in July 2020. This was primarily driven by an increase in the share of 'Minor Injury' crashes, which accounted for 12.4% of collisions compared to 10.5% in the prior year.
Severity is per crash event (most severe injury). 26 fatal crash events resulted in 25 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2020-07-01 to 2020-07-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2020-07-01 to 2020-07-31 · Most severe injury per crash record
Road & Environmental Conditions
The distribution of crashes across environmental conditions remained highly consistent year-over-year. In both July 2020 and July 2019, the vast majority of crashes occurred in clear weather (88.0% and 89.6%, respectively) and on dry road surfaces (90.4% and 90.6%, respectively). There was no significant shift in the proportion of crashes occurring in adverse weather, lighting, or road surface conditions.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2020-07-01 to 2020-07-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2020-07-01 to 2020-07-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2020-07-01 to 2020-07-31 · Road surface condition field
Vehicles & Demographics
The ranking of the top five vehicle makes involved in crashes—Honda, Toyota, Ford, Nissan, and Chevrolet—was identical in both periods, though the total count for each make decreased in line with the overall trend. An analysis of persons involved in crashes shows a slight shift in age distribution; the 16-20 age group's share of involved persons increased from 9.1% to 10.6%, while the 65+ age group's share decreased from 10.1% to 9.0%.
Top Vehicle Makes (13,143 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2020-07-01 to 2020-07-31 · Vehicle unit records
1,343 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (15,706 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2020-07-01 to 2020-07-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes became more concentrated in lower speed zones in July 2020, with areas posted at 35 mph or less accounting for 69.5% of incidents with a recorded speed limit, up from 64.9% in the prior year. Despite a decrease in total crash volume, the fatal crash rate within certain speed zones increased. For example, the rate of fatal crashes in 35 mph zones rose from 0.096% to 1.084%, and the rate in 55 mph zones increased from 0.221% to 0.783%.
Fatal crashes by zone: 1 mph: 1 of 862 (0.116%) · 25 mph: 6 of 2,341 (0.256%) · 30 mph: 4 of 556 (0.719%) · 35 mph: 9 of 830 (1.084%) · 40 mph: 1 of 342 (0.292%) · 45 mph: 1 of 281 (0.356%) · 55 mph: 4 of 511 (0.783%)
Source: Connecticut Crash Data · Csv Open Data · 2020-07-01 to 2020-07-31 · 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: 2020-07-01 through 2020-07-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2020-07-01 through 2020-07-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 6,977
- Total persons involved: 16,930
- Total vehicles involved: 13,143
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: July 2020." Published August 20, 2026. Reporting period: 2020-07-01 to 2020-07-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/july-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: 2020-07-01 – 2020-07-31
Generated: August 20, 2026 · All rights reserved
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