SponsoredThatCarHitMe.com

If you're a data point in this report, call us.

We'll evaluate whether you have a case. Free, and no pressure.

(888) 988-8341Free for accident victims

Monthly Traffic Safety Analysis

7,663 CRASHES IN
CONNECTICUT, CT
AUGUST 2020

All metrics benchmarked againstAugust 2019

In August 2020, Connecticut recorded 7,663 total traffic crashes, a 15.9% decrease from the 9,114 crashes reported in August 2019. This year-over-year decline was also reflected in fatalities, which fell from 38 to 28, and total injuries, which dropped from 3,356 to 2,958. The most significant shift was the overall reduction in crash volume across the state.

7,663

▼ -15.9%was 9,114

Total Crash Events

▼ -26.3%was 38

Persons Killed

2,958

▼ -11.9%was 3,356

Persons Injured

1,099

▲ 1.5%was 1,083

Hit-and-Run Crashes

Note: "Persons Killed" (28) counts individual fatalities across all crash events. "Fatal" in the severity table below (28) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Connecticut Crash Data · Csv Open Data · 2020-08-01 to 2020-08-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, traffic safety metrics showed a downward trend in August 2020 compared to the same month in the prior year. Total crashes decreased by 15.9%, from 9,114 to 7,663. This trend extended to crash outcomes, with total fatalities dropping by 26.3% and total injuries declining by 11.9%.

1,099

Hit-and-Run Crashes — August 2020

▲ 1.5% vs prior (1,083)

Despite an overall decrease in total crashes, the number of hit-and-run incidents slightly increased from 1,083 in August 2019 to 1,099 in August 2020. This resulted in a notable increase in the hit-and-run rate, which climbed from 11.9% to 14.3% of all crashes. This indicates that hit-and-run events constituted a larger proportion of total incidents in the current period compared to the prior year.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 9↓-44.4%

Cyclists Killed

Prior: 1→0.0%

Motorists Killed

Prior: 28↓-21.4%

Pedestrians Injured

Prior: 123↓-44.7%

Cyclists Injured

Prior: 42↑4.8%

2,846

Motorists Injured

Prior: 3,189↓-10.8%

Source: Connecticut Crash Data · Csv Open Data · 2020-08-01 to 2020-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal crash patterns shifted between the two periods. In August 2020, the peak day for crashes was Saturday with 1,235 incidents, a change from Friday (1,665 incidents) in the prior year. The peak hour for crashes also shifted slightly earlier, from 5 p.m. in 2019 to 4 p.m. in 2020, with a lower volume of 640 crashes compared to 812 in the previous year's peak hour.

Source: Connecticut Crash Data · Csv Open Data · 2020-08-01 to 2020-08-31 · Crash date field aggregated by weekday

Source: Connecticut Crash Data · Csv Open Data · 2020-08-01 to 2020-08-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the total number of fatal crashes decreased from 36 to 28 year-over-year, the proportion of crashes resulting in an injury increased. Crashes involving serious injuries rose from 1.3% to 1.8% of all incidents. Conversely, the share of crashes with no reported injuries decreased from 73.3% in August 2019 to 72.0% in August 2020, indicating that while overall crashes were down, the remaining crashes were proportionally more severe.

Outcome by Severity (Crash Events)

Fatal28fatal crashes0.4%

↓-22.2%prior 36

Serious Injury139serious injury crashes1.8%

↑19.8%prior 116

Minor Injury903minor injury crashes11.8%

↓-10.9%prior 1,013

Possible Injury1,074possible injury crashes14%

↓-15.2%prior 1,267

No Injury5,519no injury crashes72%

↓-17.4%prior 6,682

Source: Connecticut Crash Data · Csv Open Data · 2020-08-01 to 2020-08-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Connecticut Crash Data · Csv Open Data · 2020-08-01 to 2020-08-31 · Most severe injury per crash record

Road & Environmental Conditions

The distribution of crashes across environmental conditions remained largely consistent year-over-year. In both August 2020 and August 2019, crashes occurred predominantly in clear weather (88.6% and 88.0%, respectively) and on dry road surfaces (90.2% and 89.4%). Similarly, the proportion of crashes happening during daylight hours was stable, accounting for 77.0% of incidents in the current period compared to 77.8% in the prior period.

Weather

Clear6,788 (89.1%)

↓-15.3%prior 8,018

Rain480 (6.3%)

↓-30.9%prior 695

Cloudy284 (3.7%)

↓-13.9%prior 330

Severe Crosswinds45 (0.6%)

Other12 (0.2%)

Fog, Smog, Smoke10 (0.1%)

↓-50.0%prior 20

Blowing Sand, Soil, Dirt1 (0.0%)

Source: Connecticut Crash Data · Csv Open Data · 2020-08-01 to 2020-08-31 · Weather condition at time of crash

Lighting

Daylight5,898 (77.7%)

↓-16.8%prior 7,087

Dark-Lighted1,100 (14.5%)

↓-15.4%prior 1,300

Dark-Not Lighted387 (5.1%)

↓-9.2%prior 426

Dusk106 (1.4%)

↓-12.4%prior 121

Dark-Unknown Lighting45 (0.6%)

↑21.6%prior 37

Dawn45 (0.6%)

↓-21.1%prior 57

Other14 (0.2%)

↓-6.7%prior 15

Source: Connecticut Crash Data · Csv Open Data · 2020-08-01 to 2020-08-31 · Lighting condition field

Road Surface

Dry6,911 (90.7%)

↓-15.2%prior 8,148

Wet692 (9.1%)

↓-22.4%prior 892

Mud, Dirt, Gravel8 (0.1%)

↓-33.3%prior 12

Other5 (0.1%)

Moving Water1 (0.0%)

↓-83.3%prior 6

Sand1 (0.0%)

Oil1 (0.0%)

Source: Connecticut Crash Data · Csv Open Data · 2020-08-01 to 2020-08-31 · Road surface condition field

Vehicles & Demographics

The composition of vehicles involved in crashes remained stable year-over-year. The top five most common vehicle makes were Honda, Toyota, Ford, Nissan, and Chevrolet in both August 2020 and August 2019, with each seeing a reduction in total incidents. Similarly, the age distribution of persons involved in crashes showed little change, with the 26-34 age group consistently being the most represented demographic in both periods.

Top Vehicle Makes (14,517 vehicles)

HONDA1,544 (10.6%)

↓-13.6%prior 1,788

TOYOTA1,387 (9.6%)

↓-17.5%prior 1,681

FORD1,316 (9.1%)

↓-14.3%prior 1,535

NISSAN1,163 (8%)

↓-17.0%prior 1,401

CHEVROLET843 (5.8%)

↓-19.2%prior 1,043

JEEP584 (4%)

↓-6.4%prior 624

HYUNDAI569 (3.9%)

↓-5.2%prior 600

SUBARU553 (3.8%)

↓-25.0%prior 737

DODGE334 (2.3%)

↓-18.3%prior 409

BMW315 (2.2%)

↓-12.7%prior 361

Source: Connecticut Crash Data · Csv Open Data · 2020-08-01 to 2020-08-31 · Vehicle unit records

1,445 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (17,309 persons with recorded sex)

Male9,985 (57.7%)

↓-15.2%prior 11,774

Female7,323 (42.3%)

↓-25.0%prior 9,761

01 (0.0%)

Source: Connecticut Crash Data · Csv Open Data · 2020-08-01 to 2020-08-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes decreased across most speed zones, with the 25 mph zone remaining the most frequent location for incidents in both periods (2,452 in 2020 vs. 2,865 in 2019). The number of fatal crashes in 25 mph zones dropped from 10 to 4. In contrast, while the total number of crashes in 65 mph zones fell from 526 to 378, the number of fatal crashes remained constant at 4, causing the fatality rate for that speed zone to increase from 0.76% to 1.06%.

Fatal crashes by zone: 1 mph: 1 of 809 (0.124%) · 25 mph: 4 of 2,452 (0.163%) · 30 mph: 4 of 633 (0.632%) · 35 mph: 5 of 974 (0.513%) · 40 mph: 2 of 438 (0.457%) · 45 mph: 2 of 308 (0.649%) · 50 mph: 2 of 201 (0.995%) · 55 mph: 4 of 596 (0.671%) · 65 mph: 4 of 378 (1.058%)

Source: Connecticut Crash Data · Csv Open Data · 2020-08-01 to 2020-08-31 · 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: 2020-08-01 through 2020-08-31
Report generated: August 20, 2026

Data Coverage

Reporting period: 2020-08-01 through 2020-08-31 (31 days)
Geographic scope: connecticut, CT
Total crash records analyzed: 7,663
Total persons involved: 18,675
Total vehicles involved: 14,517

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: August 2020." Published August 20, 2026. Reporting period: 2020-08-01 to 2020-08-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/august-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