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Yearly Traffic Safety Analysis

26,265 CRASHES IN
CONNECTICUT, CT
2025

All metrics benchmarked against2024

In 2025, Hartford County recorded 26,265 total crashes, a slight increase of 0.5% from the 26,137 crashes reported in 2024. Despite the minor rise in overall incidents, the most significant year-over-year change was a 27.8% decrease in total fatalities, which fell from 90 in the prior period to 65 in the current period.

26,265

▲ 0.5%was 26,137

Total Crash Events

▼ -27.8%was 90

Persons Killed

8,445

▼ -6.4%was 9,023

Persons Injured

3,634

▲ 3.6%was 3,508

Hit-and-Run Crashes

Note: "Persons Killed" (65) counts individual fatalities across all crash events. "Fatal" in the severity table below (55) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall crash trend in Hartford County remained relatively stable year-over-year, with a marginal 0.5% increase from 26,137 crashes in 2024 to 26,265 in 2025. However, the severity of these incidents decreased, as total injuries fell by 6.4% and total fatalities saw a substantial 27.8% decline.

3,634

Hit-and-Run Crashes — 2025

▲ 3.6% vs prior (3,508)

Hit-and-run incidents increased in both count and rate compared to the previous year. The total number of hit-and-run crashes rose from 3,508 in 2024 to 3,634 in 2025. This represents an increase in the hit-and-run rate from 13.4% of all crashes in the prior period to 13.8% in the current period.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 21↓-14.3%

Cyclists Killed

Prior: 2→0.0%

Motorists Killed

Prior: 67↓-32.8%

282

Pedestrians Injured

Prior: 324↓-13.0%

Cyclists Injured

Prior: 88↑11.4%

8,065

Motorists Injured

Prior: 8,611↓-6.3%

Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal crash patterns remained consistent year-over-year, with Friday being the peak day for crashes in both 2025 (4,330 crashes) and 2024 (4,263 crashes). Similarly, the 4 p.m. hour was the peak time for incidents in both periods, with 2,387 crashes in the current year compared to 2,423 in the prior year. The overall distribution of crashes by day and hour showed no significant shifts between the two periods.

Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes decreased from 2024 to 2025. The fatal crash rate fell from 0.3% of all crashes to 0.2%, with 55 fatal incidents in the current period compared to 85 in the prior. The proportion of crashes resulting in minor injuries also decreased from 12.8% to 12.2%, while the share of non-injury crashes increased from 75.4% to 76.1%.

Severity is per crash event (most severe injury). 55 fatal crash events resulted in 65 persons killed.

Outcome by Severity (Crash Events)

Fatal55fatal crashes0.2%

↓-35.3%prior 85

Serious Injury313serious injury crashes1.2%

↑5.0%prior 298

Minor Injury3,195minor injury crashes12.2%

↓-4.6%prior 3,349

Possible Injury2,702possible injury crashes10.3%

↓-0.3%prior 2,710

No Injury20,000no injury crashes76.1%

↑1.5%prior 19,695

Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The environmental conditions under which crashes occurred were largely consistent between the two periods. In both years, the vast majority of crashes happened in clear weather (83.6% in 2025 vs. 82.7% in 2024) and on dry roads (82.1% vs. 81.8%). Crashes during daylight hours also remained stable, accounting for approximately 70% of incidents in both periods. There was a small decrease in the proportion of crashes on wet roads, from 14.4% in 2024 to 13.2% in 2025.

Weather

Clear21,949 (83.9%)

↑1.5%prior 21,615

Rain2,350 (9.0%)

↓-9.2%prior 2,588

Cloudy904 (3.5%)

↓-2.9%prior 931

Snow551 (2.1%)

↓-0.9%prior 556

Freezing Rain or Freezing Drizzle194 (0.7%)

↑26.0%prior 154

Blowing Snow84 (0.3%)

↓-16.0%prior 100

Fog, Smog, Smoke51 (0.2%)

↑15.9%prior 44

Sleet or Hail34 (0.1%)

↑47.8%prior 23

Other23 (0.1%)

↑64.3%prior 14

Severe Crosswinds6 (0.0%)

↑20.0%prior 5

Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight18,499 (70.8%)

↑1.2%prior 18,271

Dark-Lighted5,983 (22.9%)

↓-0.6%prior 6,022

Dark-Not Lighted929 (3.6%)

↓-6.5%prior 994

Dusk304 (1.2%)

↑0.3%prior 303

Dawn193 (0.7%)

↑2.1%prior 189

Dark-Unknown Lighting164 (0.6%)

↓-3.0%prior 169

Other45 (0.2%)

↓-15.1%prior 53

Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry21,562 (82.5%)

↑0.9%prior 21,374

Wet3,479 (13.3%)

↓-7.4%prior 3,758

Snow490 (1.9%)

↑9.6%prior 447

Ice / Frost345 (1.3%)

↑45.6%prior 237

Slush219 (0.8%)

↑36.0%prior 161

Other15 (0.1%)

↓-11.8%prior 17

Moving Water14 (0.1%)

↑7.7%prior 13

Mud, Dirt, Gravel13 (0.0%)

→0.0%prior 13

Standing Water7 (0.0%)

↓-22.2%prior 9

Sand6 (0.0%)

Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The top five vehicle makes involved in crashes—Honda, Toyota, Ford, Nissan, and Chevrolet—were the same in both 2025 and 2024, with very similar involvement counts year-over-year. The age distribution of persons involved in crashes also showed little change. The 26-34 and 35-44 age groups continued to be the most frequently involved, with their representation remaining stable across both periods.

Top Vehicle Makes (50,046 vehicles)

HONDA4,951 (9.9%)

↓-2.6%prior 5,083

TOYOTA4,776 (9.5%)

↑0.5%prior 4,754

FORD4,181 (8.4%)

↑0.1%prior 4,176

NISSAN3,002 (6%)

↓-1.6%prior 3,051

CHEVROLET2,316 (4.6%)

↓-6.1%prior 2,466

SUBARU2,201 (4.4%)

↑3.6%prior 2,125

HYUNDAI1,827 (3.7%)

↑2.2%prior 1,787

JEEP1,826 (3.6%)

↓-4.4%prior 1,911

HOND1,707 (3.4%)

↑4.2%prior 1,638

TOYT1,482 (3%)

↓-1.1%prior 1,499

Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

3,938 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (59,016 persons with recorded sex)

Male33,250 (56.3%)

↓-0.3%prior 33,361

Female25,766 (43.7%)

↓-2.2%prior 26,352

Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across different speed zones saw minor shifts, with a slight decrease in incidents in 25 mph zones (4,299 vs. 4,468) and a slight increase in 65 mph zones (3,043 vs. 2,869). More notably, the number of fatal crashes dropped significantly in several key speed zones. Fatal crashes in 35 mph zones fell from 18 to 6, and fatal crashes in 65 mph zones decreased from 19 in the prior year to just 2 in the current year.

Fatal crashes by zone: 1 mph: 3 of 1,412 (0.212%) · 25 mph: 6 of 4,299 (0.14%) · 30 mph: 15 of 2,693 (0.557%) · 35 mph: 6 of 4,126 (0.145%) · 40 mph: 6 of 2,085 (0.288%) · 45 mph: 5 of 925 (0.541%) · 50 mph: 5 of 1,759 (0.284%) · 55 mph: 3 of 839 (0.358%) · 65 mph: 2 of 3,043 (0.066%) · 88 mph: 3 of 1,532 (0.196%) · 99 mph: 1 of 243 (0.412%)

Source: Connecticut Crash Data · Csv Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
Report generated: August 21, 2026

Data Coverage

Reporting period: 2025-01-01 through 2025-12-31 (365 days)
Geographic scope: connecticut, CT
Total crash records analyzed: 26,265
Total persons involved: 63,051
Total vehicles involved: 50,046

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: 2025." Published August 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Connecticut Crash Data, Csv Open Data. Available at: https://thatcarhitme.com/crash-data/connecticut/statewide/2025-annual-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

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