If you're a data point in this report, call us.
We'll evaluate whether you have a case. Free, and no pressure.
ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CONNECTICUT, CT · JULY 2022
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-2022-report
Monthly Traffic Safety Analysis
8,224 CRASHES IN
CONNECTICUT, CT
JULY 2022
In July 2022, Connecticut recorded 8,224 motor vehicle crashes, a 5.5% decrease from the 8,698 crashes reported in July 2021. Despite the overall reduction in collisions, the number of fatalities increased by 12.9%, rising from 31 to 35 year-over-year. The most notable shift was a 43.8% decrease in speeding-related crashes, which fell from 653 to 367.
8,224
▼ -5.4%was 8,698
Total Crash Events
35
▲ 12.9%was 31
Persons Killed
3,056
▼ -2.7%was 3,142
Persons Injured
1,109
▼ -1.8%was 1,129
Hit-and-Run Crashes
Note: "Persons Killed" (35) counts individual fatalities across all crash events. "Fatal" in the severity table below (34) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Connecticut Crash Data · Csv Open Data · 2022-07-01 to 2022-07-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash and injury trends show a decrease in July 2022 compared to the previous year. Total crashes fell by 474 (a 5.5% reduction), and total injuries decreased by 86 (a 2.7% reduction). However, this downward trend did not extend to fatalities, which increased by 12.9% from 31 to 35 deaths.
1,109
Hit-and-Run Crashes — July 2022
▼ -1.8% vs prior (1,129)
The total number of hit-and-run crashes decreased slightly from 1,129 in July 2021 to 1,109 in July 2022. However, because total crashes decreased at a greater rate, the proportion of all crashes classified as hit-and-run trended upward. The hit-and-run rate increased from 13.0% to 13.5% year-over-year.
Vulnerable Road User Casualties
3
Pedestrians Killed
1
Cyclists Killed
31
Motorists Killed
76
Pedestrians Injured
40
Cyclists Injured
2,940
Motorists Injured
Source: Connecticut Crash Data · Csv Open Data · 2022-07-01 to 2022-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained largely consistent year-over-year. Friday was the peak day for crashes in both July 2022 (1,586 crashes) and July 2021 (1,722 crashes), and the 4 PM hour was the peak hour in both periods. While overall crash volumes decreased, the distribution of crashes throughout the week and day did not experience a significant shift.
Source: Connecticut Crash Data · Csv Open Data · 2022-07-01 to 2022-07-31 · Crash date field aggregated by weekday
Source: Connecticut Crash Data · Csv Open Data · 2022-07-01 to 2022-07-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes declined, the severity of crashes increased in July 2022 compared to the prior year. The number of fatal crashes rose from 30 to 34, and the fatal crash rate increased from 0.34% to 0.41%. Crashes resulting in minor injuries also increased proportionally from 11.5% to 12.7% of all collisions, while those with possible or no injuries saw a proportional decrease.
Severity is per crash event (most severe injury). 34 fatal crash events resulted in 35 persons killed.
Outcome by Severity (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-07-01 to 2022-07-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Connecticut Crash Data · Csv Open Data · 2022-07-01 to 2022-07-31 · Most severe injury per crash record
Road & Environmental Conditions
Driving conditions were markedly different between the two periods, with a significant reduction in adverse weather-related crashes in July 2022. Crashes occurring in rain dropped from 1,238 to 326, and collisions on wet road surfaces fell from 1,637 to 445. Consequently, the proportion of crashes on dry roads rose from 79.8% in July 2021 to 93.6% in July 2022.
Weather
Source: Connecticut Crash Data · Csv Open Data · 2022-07-01 to 2022-07-31 · Weather condition at time of crash
Lighting
Source: Connecticut Crash Data · Csv Open Data · 2022-07-01 to 2022-07-31 · Lighting condition field
Road Surface
Source: Connecticut Crash Data · Csv Open Data · 2022-07-01 to 2022-07-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes remained consistent, with Honda, Toyota, and Ford being the top three in both July 2022 and July 2021. The age distribution of persons involved in crashes showed a slight shift, with a small proportional decrease for the 16-20 and 26-34 age groups. Conversely, there was a minor proportional increase in persons aged 35 and older.
Top Vehicle Makes (15,605 vehicles)
Source: Connecticut Crash Data · Csv Open Data · 2022-07-01 to 2022-07-31 · Vehicle unit records
1,279 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (18,439 persons with recorded sex)
Source: Connecticut Crash Data · Csv Open Data · 2022-07-01 to 2022-07-31 · Person-level records linked to crash events
Speed Limit Zones
Year-over-year, crashes saw a larger decrease in lower speed zones (35 mph or less) compared to higher speed zones. Despite the drop in total crashes, the fatality rate within several specific zones increased. For instance, in 55 mph zones, the number of fatal crashes rose from 4 to 7, increasing the fatality rate for that zone from 0.47% to 0.80%.
Fatal crashes by zone: 25 mph: 7 of 2,349 (0.298%) · 30 mph: 3 of 624 (0.481%) · 35 mph: 6 of 875 (0.686%) · 40 mph: 4 of 455 (0.879%) · 45 mph: 3 of 299 (1.003%) · 50 mph: 1 of 201 (0.498%) · 55 mph: 7 of 877 (0.798%) · 65 mph: 3 of 487 (0.616%)
Source: Connecticut Crash Data · Csv Open Data · 2022-07-01 to 2022-07-31 · 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: 2022-07-01 through 2022-07-31
- Report generated: August 20, 2026
Data Coverage
- Reporting period: 2022-07-01 through 2022-07-31 (31 days)
- Geographic scope: connecticut, CT
- Total crash records analyzed: 8,224
- Total persons involved: 19,891
- Total vehicles involved: 15,605
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 2022." Published August 20, 2026. Reporting period: 2022-07-01 to 2022-07-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/july-2022-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: 2022-07-01 – 2022-07-31
Generated: August 20, 2026 · All rights reserved
The data is step one. Get a Connecticut attorney on the line.
Call our intake team. We connect you to a vetted Connecticut personal injury attorney who calls you back within minutes. No phone tag. No voicemails.
Always free for accident victims.