Yearly Traffic Safety Analysis

564 CRASHES IN
YARMOUTH, MA
2025

All metrics benchmarked against2024

In 2025, Yarmouth recorded 564 total traffic crashes, an 8.1% decrease from the 614 crashes reported in 2024. Despite the overall decline in collisions, the number of fatalities increased from 2 in 2024 to 5 in 2025, and the number of fatal crashes rose from 1 to 5.

564

-8.1%was 614

Total Crash Events

5

150.0%was 2

Persons Killed

168

-20.4%was 211

Persons Injured

29

-9.4%was 32

Hit-and-Run Crashes

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 10 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 Yarmouth showed a downward trend, decreasing by 8.1% from 614 in 2024 to 564 in 2025. This trend included a 20.4% reduction in total injuries, which fell from 211 to 168. However, fatalities more than doubled, rising from 2 in the prior year to 5 in the current year.

29

Hit-and-Run Crashes — 2025

-9.4% vs prior (32)

The number of hit-and-run incidents saw a slight decrease, from 32 in 2024 to 29 in 2025. As a proportion of total collisions, the hit-and-run rate remained stable, moving from 5.2% in the prior year to 5.1% in the current year. This indicates no significant change in the trend of hit-and-run crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

5

Motorists Killed

Prior: 2150.0%

0

Other Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 4-25.0%

12

Cyclists Injured

Prior: 15-20.0%

148

Motorists Injured

Prior: 187-20.9%

5

Other Injured

Prior: 50.0%

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 remained largely consistent year-over-year. Thursday was the peak day for crashes in both 2025 (101 crashes) and 2024 (102 crashes). The peak hour for collisions shifted slightly earlier, from 4 PM in 2024 (53 crashes) to 3 PM in 2025 (55 crashes), with the afternoon commute period remaining the most frequent time for incidents.

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

While total crashes decreased, the severity of collisions increased from 2024 to 2025. The number of fatal crashes rose from 1 to 5, and the fatal crash rate increased from 0.16% to 0.89%. The proportion of serious injury crashes also grew from 2.1% (13 crashes) to 2.8% (16 crashes), while crashes resulting in minor or possible injuries saw a decline in both their absolute counts and their share of total incidents.

Outcome by Severity (Crash Events)

Fatal5fatal crashes0.9%
400.0%prior 1
Serious Injury16serious injury crashes2.8%
23.1%prior 13
Minor Injury79minor injury crashes14%
-24.8%prior 105
Possible Injury34possible injury crashes6%
-17.1%prior 41
No Injury420no injury crashes74.5%
-3.0%prior 433

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

The top three contributing factors cited in crashes remained unchanged between 2024 and 2025: Inattention, No improper driving, and Failed to yield right of way. While the count of crashes attributed to 'Inattention' decreased by 23.3% (from 150 to 115), it remained the leading factor. A notable shift was observed in 'Failure to keep in proper lane or running off road,' where the count of associated crashes increased by 77.8%, from 18 in 2024 to 32 in 2025.

Officer-Reported Primary Contributing Cause

Inattention115 (20.4%)-23.3%prior 150
No improper driving105 (18.6%)-3.7%prior 109
Failed to yield right of way89 (15.8%)-4.3%prior 93
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner36 (6.4%)5.9%prior 34
Followed too closely36 (6.4%)-21.7%prior 46
Failure to keep in proper lane or running off road32 (5.7%)77.8%prior 18
Other improper action19 (3.4%)58.3%prior 12
Disregarded traffic signs, signals, road markings12 (2.1%)-40.0%prior 20
Distracted12 (2.1%)33.3%prior 9
Over-correcting/over-steering8 (1.4%)60.0%prior 5

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

The majority of crashes in both periods occurred in clear weather and on dry roads, with proportions remaining stable year-over-year. In 2025, 68.8% of crashes happened in clear weather, compared to 69.4% in 2024. Similarly, 83.3% of crashes in 2025 were on dry road surfaces, versus 83.9% in the prior year. There was a slight increase in the proportion of crashes occurring during daylight hours, which rose from 72.3% in 2024 to 77.1% in 2025.

Weather

Clear388 (69.0%)
-8.9%prior 426
Cloudy61 (10.9%)
-21.8%prior 78
Clear/Clear30 (5.3%)
275.0%prior 8
Rain29 (5.2%)
-17.1%prior 35
Snow14 (2.5%)
40.0%prior 10
Cloudy/Rain11 (2.0%)
-21.4%prior 14
Clear/Other6 (1.1%)
-50.0%prior 12
Cloudy/Other5 (0.9%)
Clear/Cloudy4 (0.7%)
Rain/Cloudy3 (0.5%)
-40.0%prior 5

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

Lighting

Daylight435 (77.5%)
-2.0%prior 444
Dark - lighted roadway60 (10.7%)
-29.4%prior 85
Dark - roadway not lighted42 (7.5%)
-14.3%prior 49
Dusk15 (2.7%)
-11.8%prior 17
Dark - unknown roadway lighting5 (0.9%)
-54.5%prior 11
Dawn4 (0.7%)

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

Road Surface

Dry470 (83.8%)
-8.7%prior 515
Wet70 (12.5%)
-11.4%prior 79
Snow15 (2.7%)
25.0%prior 12
Ice3 (0.5%)
Slush2 (0.4%)
Water (standing, moving)1 (0.2%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes remained consistent, with Toyota, Ford, and Honda as the top three in both 2024 and 2025. The number of Toyotas involved decreased from 217 to 195, while Fords increased from 118 to 137. An analysis of persons involved in crashes shows a stable age distribution, though the proportion of individuals aged 65 and older increased slightly from 19.1% of all persons in 2024 to 20.3% in 2025.

Top Vehicle Makes (1,022 vehicles)

1
TOYOTA195 (19.1%)
-10.1%prior 217
2
FORD137 (13.4%)
16.1%prior 118
3
HONDA107 (10.5%)
-4.5%prior 112
4
CHEVROLET77 (7.5%)
-16.3%prior 92
5
JEEP52 (5.1%)
-18.8%prior 64
6
NISSAN46 (4.5%)
-20.7%prior 58
7
KIA41 (4%)
0.0%prior 41
8
HYUNDAI38 (3.7%)
-22.4%prior 49
9
GMC29 (2.8%)
-39.6%prior 48
10
VOLKSWAGEN29 (2.8%)
45.0%prior 20

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

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

Sex Distribution (1,180 persons with recorded sex)

Male647 (54.8%)
-12.1%prior 736
Female533 (45.2%)
-5.7%prior 565

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

Crashes were most prevalent in speed zones between 30 and 40 mph in both years, with the 40 mph zone recording the highest number of incidents in 2025 (161 crashes) and 2024 (163 crashes). A significant year-over-year change was observed in the location of fatal crashes. In 2024, the single fatal crash occurred in a 35 mph zone, whereas in 2025, all 5 fatal crashes occurred in a 40 mph zone.

Fatal crashes by zone: 40 mph: 5 of 161 (3.106%)

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: YARMOUTH, MA
  • Total crash records analyzed: 564
  • Total persons involved: 1,255
  • Total vehicles involved: 1,022

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). "YARMOUTH, 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/yarmouth/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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Yarmouth, MA Crash Report — 2025 | ThatCarHitMe.com