Yearly Traffic Safety Analysis

103,422 CRASHES IN
CONNECTICUT, CT
2025

All metrics benchmarked against2024

In 2025, Connecticut recorded 103,422 total crashes, a slight decrease of 0.8% from 104,259 in 2024. Despite the stable crash volume, the state saw a significant year-over-year decrease in traffic fatalities, which fell 21.8% from 317 to 248. This sharp drop in the number of people killed in crashes represents the most notable shift in the data.

103,422

▼ -0.8%was 104,259

Total Crash Events

248

▼ -21.8%was 317

Persons Killed

31,554

▼ -5.4%was 33,355

Persons Injured

13,345

▲ 1.6%was 13,135

Hit-and-Run Crashes

Note: "Persons Killed" (248) counts individual fatalities across all crash events. "Fatal" in the severity table below (217) 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 trend shows a relatively stable number of total crashes, with a decrease of less than 1% from 104,259 in 2024 to 103,422 in 2025. However, the severity of these incidents lessened, as total injuries fell by 5.4% from 33,355 to 31,554, and total fatalities dropped by a significant 21.8% from 317 to 248.

13,345

Hit-and-Run Crashes — 2025

▲ 1.6% vs prior (13,135)

The number of hit-and-run crashes increased from 13,135 in 2024 to 13,345 in 2025. As a percentage of all crashes, the hit-and-run rate also trended slightly upward, rising from 12.6% to 12.9% year-over-year.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 63↓-14.3%

Cyclists Killed

Prior: 4↑25.0%

189

Motorists Killed

Prior: 249↓-24.1%

Other Killed

Prior: 1↓-100.0%

1,151

Pedestrians Injured

Prior: 1,300↓-11.5%

349

Cyclists Injured

Prior: 355↓-1.7%

30,051

Motorists Injured

Prior: 31,700↓-5.2%

Other Injured

Prior: 0→%

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 largely consistent year-over-year. Friday was the peak day for crashes in both periods, with 16,902 incidents in 2025 compared to 16,901 in 2024. A minor shift occurred in the peak hour for crashes, moving from the 3 p.m. hour in 2024 (8,762 crashes) to the 4 p.m. hour in 2025 (8,723 crashes).

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 the prior year. Fatal crashes fell from 288 to 217, representing a drop from 0.3% to 0.2% of all crashes. The proportion of crashes involving minor injuries also declined slightly from 11.5% to 11.2%. Correspondingly, crashes with no reported injuries increased as a share of the total, rising from 76.4% in 2024 to 77.1% in 2025.

Severity is per crash event (most severe injury). 217 fatal crash events resulted in 248 persons killed.

Outcome by Severity (Crash Events)

Fatal217fatal crashes0.2%

↓-24.7%prior 288

Serious Injury1,286serious injury crashes1.2%

↓-1.7%prior 1,308

Minor Injury11,562minor injury crashes11.2%

↓-3.4%prior 11,964

Possible Injury10,609possible injury crashes10.3%

↓-4.1%prior 11,058

No Injury79,748no injury crashes77.1%

↑0.1%prior 79,641

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

Crash conditions were very similar between the two periods. The vast majority of incidents in both years occurred in clear weather (83.1% in 2025 vs. 82.9% in 2024) and on dry road surfaces (82.1% vs. 82.4%). The proportion of crashes taking place in daylight was also stable at approximately 70%. One minor shift was an increase in crashes on snow-covered roads, from 2,373 in 2024 to 2,942 in 2025.

Weather

Clear85,962 (83.5%)

↓-0.5%prior 86,425

Rain8,581 (8.3%)

↓-11.2%prior 9,666

Cloudy3,946 (3.8%)

↑0.2%prior 3,937

Snow2,942 (2.9%)

↑24.0%prior 2,373

Freezing Rain or Freezing Drizzle616 (0.6%)

↑12.0%prior 550

Blowing Snow423 (0.4%)

↑18.5%prior 357

Fog, Smog, Smoke250 (0.2%)

↑14.7%prior 218

Sleet or Hail101 (0.1%)

↓-1.9%prior 103

Other83 (0.1%)

↑29.7%prior 64

Severe Crosswinds45 (0.0%)

↑28.6%prior 35

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

Lighting

Daylight72,632 (70.7%)

↓-0.2%prior 72,754

Dark-Lighted21,140 (20.6%)

↓-1.4%prior 21,442

Dark-Not Lighted6,224 (6.1%)

↓-3.6%prior 6,458

Dusk1,212 (1.2%)

↓-6.8%prior 1,300

Dark-Unknown Lighting717 (0.7%)

↑9.1%prior 657

Dawn697 (0.7%)

↓-3.3%prior 721

Other160 (0.2%)

↓-19.2%prior 198

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

Road Surface

Dry84,894 (82.5%)

↓-1.2%prior 85,895

Wet12,859 (12.5%)

↓-7.4%prior 13,890

Snow2,622 (2.5%)

↑40.9%prior 1,861

Ice / Frost1,575 (1.5%)

↑34.2%prior 1,174

Slush772 (0.7%)

↑25.3%prior 616

Mud, Dirt, Gravel79 (0.1%)

↓-11.2%prior 89

Other52 (0.1%)

↓-16.1%prior 62

Moving Water36 (0.0%)

↓-33.3%prior 54

Standing Water31 (0.0%)

↓-42.6%prior 54

Sand30 (0.0%)

↓-25.0%prior 40

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—remained unchanged in their ranking year-over-year. The distribution of persons involved in crashes by age group also showed little change; the 26-34 age group remained the largest cohort in both periods, decreasing slightly from 41,472 individuals to 40,481. The total number of vehicles involved in crashes decreased from 196,510 to 195,355.

Top Vehicle Makes (195,355 vehicles)

HONDA21,693 (11.1%)

↓-2.0%prior 22,134

TOYOTA21,244 (10.9%)

↓-0.1%prior 21,272

FORD16,649 (8.5%)

↓-3.1%prior 17,176

NISSAN13,250 (6.8%)

↓-3.0%prior 13,665

CHEVROLET11,763 (6%)

↓-2.5%prior 12,059

SUBARU9,771 (5%)

↑2.2%prior 9,565

JEEP8,565 (4.4%)

↑0.4%prior 8,530

HYUNDAI8,202 (4.2%)

↑0.3%prior 8,177

KIA5,034 (2.6%)

↑5.0%prior 4,796

BMW4,501 (2.3%)

↑0.7%prior 4,468

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

14,699 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (226,597 persons with recorded sex)

Male129,426 (57.1%)

↓-1.6%prior 131,470

Female97,171 (42.9%)

↓-2.6%prior 99,738

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

Speed Limit Zones

While the distribution of crashes across speed zones was stable, there was a significant reduction in fatal outcomes within several zones. In 25 mph zones, fatal crashes dropped from 82 to 47, despite a nearly identical number of total crashes. Similarly, in 65 mph zones, fatal crashes were more than halved, falling from 39 to 18. This trend of lower fatalities relative to crash volume was also observed in the 35 mph and 45 mph zones.

Fatal crashes by zone: 1 mph: 6 of 12,844 (0.047%) · 25 mph: 47 of 29,170 (0.161%) · 30 mph: 29 of 8,055 (0.36%) · 35 mph: 27 of 11,484 (0.235%) · 40 mph: 28 of 5,856 (0.478%) · 45 mph: 29 of 3,751 (0.773%) · 50 mph: 10 of 2,726 (0.367%) · 55 mph: 18 of 10,197 (0.177%) · 65 mph: 18 of 7,312 (0.246%) · 88 mph: 3 of 4,394 (0.068%) · 99 mph: 1 of 539 (0.186%)

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 3, 2026

Data Coverage

Reporting period: 2025-01-01 through 2025-12-31 (365 days)
Geographic scope: connecticut, CT
Total crash records analyzed: 103,422
Total persons involved: 244,396
Total vehicles involved: 195,355

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 3, 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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103,422 CRASHES INCONNECTICUT, CT2025