Yearly Traffic Safety Analysis

92 CRASHES IN
COHASSET, MA
2025

All metrics benchmarked against2024

In 2025, Cohasset recorded 92 total crashes, a 6.1% decrease from the 98 crashes reported in 2024. While overall crashes declined, the most significant year-over-year shift was in crash severity, with the city recording one fatality in 2025 compared to zero in the prior year. The total number of injuries also increased from 20 to 27.

92

-6.1%was 98

Total Crash Events

1

Persons Killed

27

35.0%was 20

Persons Injured

5

-54.5%was 11

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 4 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crashes in Cohasset showed a slight year-over-year decrease of 6.1%, falling from 98 incidents in 2024 to 92 in 2025. Despite the reduction in total crashes, the number of people injured increased by 35% from 20 to 27. Additionally, the city recorded one fatality in 2025, whereas there were none in the previous year.

5

Hit-and-Run Crashes — 2025

-54.5% vs prior (11)

The number of hit-and-run incidents in Cohasset saw a significant year-over-year decrease. In 2025, there were 5 hit-and-run crashes, down from 11 in 2024, representing a 54.5% reduction in count. Correspondingly, the hit-and-run rate as a percentage of total crashes fell by more than half, from 11.2% in 2024 to 5.4% in 2025.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

1

Pedestrians Injured

Prior: 0%

26

Motorists Injured

Prior: 1844.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly 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

The temporal patterns of crashes showed some shifts between the two years. The peak day for crashes moved from Thursday (22 crashes) in 2024 to Monday (16 crashes) in 2025. However, the peak hour for collisions remained consistent at 11 a.m. in both periods, with 15 crashes in 2024 and 13 in 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity worsened in 2025 compared to 2024. A fatal crash was recorded in 2025, accounting for 1.1% of all incidents, whereas no fatal crashes occurred in the prior year. The proportion of crashes resulting in any level of injury also increased, rising from 15.3% of crashes in 2024 (15 injury crashes) to 25.0% in 2025 (23 injury crashes). Notably, 2025 saw one serious injury crash, a severity category not present in the 2024 data.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1.1%
Serious Injury1serious injury crashes1.1%
Minor Injury19minor injury crashes20.7%
111.1%prior 9
Possible Injury2possible injury crashes2.2%
-66.7%prior 6
No Injury65no injury crashes70.7%
-12.2%prior 74

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

While 'No improper driving' was cited in more crashes, increasing from a count of 20 to 26, crashes attributed to 'Failed to yield right of way' decreased slightly from 16 to 14. Notably, incidents involving 'Inattention' more than doubled, with the count rising from 4 to 9. Conversely, crashes from 'Followed too closely' saw a significant drop in count from 12 in 2024 to 7 in 2025, causing it to fall out of the top three contributing factors.

Officer-Reported Primary Contributing Cause

No improper driving26 (28.3%)30.0%prior 20
Failed to yield right of way14 (15.2%)-12.5%prior 16
Failure to keep in proper lane or running off road9 (9.8%)-25.0%prior 12
Inattention9 (9.8%)
Followed too closely7 (7.6%)-41.7%prior 12
Distracted5 (5.4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (3.3%)
Other improper action3 (3.3%)
Exceeded authorized speed limit2 (2.2%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in 2025 occurred more frequently under favorable conditions compared to 2024. The proportion of crashes on dry roads increased from 73.5% to 84.8%, and those in clear weather rose from 70.4% to 82.6%. Consequently, the share of crashes happening during adverse weather (like rain or snow) decreased from 29.6% of all crashes in 2024 to 17.4% in 2025. The percentage of crashes in daylight conditions remained relatively stable between the two periods.

Weather

Clear76 (82.6%)
10.1%prior 69
Cloudy/Rain5 (5.4%)
Cloudy4 (4.3%)
-55.6%prior 9
Rain2 (2.2%)
-80.0%prior 10
Snow2 (2.2%)
Rain/Cloudy1 (1.1%)
Snow/Blowing sand, snow1 (1.1%)
Clear/Cloudy1 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight70 (76.1%)
-11.4%prior 79
Dark - lighted roadway12 (13.0%)
-20.0%prior 15
Dark - roadway not lighted7 (7.6%)
Dusk3 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry78 (84.8%)
8.3%prior 72
Wet9 (9.8%)
-52.6%prior 19
Ice2 (2.2%)
Snow2 (2.2%)
Water (standing, moving)1 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

Toyota and Ford remained the top two vehicle makes involved in crashes for both periods, though their counts decreased from 25 to 20 and 20 to 14, respectively. Regarding persons involved, the 65+ age group was the largest demographic in both years, growing from 41 individuals in 2024 to 47 in 2025. In contrast, the number of individuals in the 16-20 age group involved in crashes saw a notable decrease from 30 to 17.

Top Vehicle Makes (160 vehicles)

1
TOYOTA20 (12.5%)
-20.0%prior 25
2
HONDA16 (10%)
45.5%prior 11
3
FORD14 (8.8%)
-30.0%prior 20
4
CHEVROLET14 (8.8%)
16.7%prior 12
5
JEEP10 (6.3%)
25.0%prior 8
6
GMC8 (5%)
0.0%prior 8
7
NISSAN8 (5%)
60.0%prior 5
8
MERCEDES-BENZ7 (4.4%)
9
KIA6 (3.8%)
20.0%prior 5
10
VOLKSWAGEN6 (3.8%)
0.0%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

21 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (186 persons with recorded sex)

Female94 (50.5%)
3.3%prior 91
Male92 (49.5%)
0.0%prior 92

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

In both years, the 25 mph speed zone was the site of the most crashes, though the number of incidents in this zone decreased from 34 in 2024 to 24 in 2025. Crashes also decreased in the 30 mph zone, from 17 to 13. The single fatal crash recorded in 2025 occurred in a 35 mph zone, which had 13 total crashes that year, compared to 14 crashes and no fatalities in that same zone the previous year.

Fatal crashes by zone: 35 mph: 1 of 13 (7.692%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly 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 Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly 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: Arcgis_yearly 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: June 21, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: COHASSET, MA
  • Total crash records analyzed: 92
  • Total persons involved: 203
  • Total vehicles involved: 160

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). "COHASSET, MA Crash Intelligence Report: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/cohasset/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

ThatCarHitMe.com · An Injuria.ai Company

Cohasset, MA Crash Report — 2025 | ThatCarHitMe.com