Monthly Traffic Safety Analysis

42 CRASHES IN
YARMOUTH, MA
SEPTEMBER 2025

All metrics benchmarked againstSeptember 2024

In Yarmouth, September 2025 saw a notable decrease in overall crash activity compared to September 2024. Total crashes declined by 23.6%, from 55 crashes in the prior period to 42 crashes in the current period. This reduction in crashes was accompanied by a 30% decrease in total injuries, falling from 20 to 14.

42

-23.6%was 55

Total Crash Events

0

Persons Killed

14

-30.0%was 20

Persons Injured

4

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a decrease in crash activity year-over-year, with total crashes falling by 13 incidents from 55 to 42. Similarly, total injuries decreased by 6, from 20 in September 2024 to 14 in September 2025. Fatalities remained at zero in both periods.

4

Hit-and-Run Crashes — September 2025

0.0% vs prior (4)

The number of hit-and-run crashes remained constant at 4 in both September 2024 and September 2025. However, due to the overall decrease in total crashes, the hit-and-run crash rate increased from 7.3% to 9.5% year-over-year.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

2

Cyclists Injured

Prior: 20.0%

12

Motorists Injured

Prior: 15-20.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Tuesday (14 crashes) in the prior period to Thursday (11 crashes) in the current period. The peak hour also changed significantly, moving from 4 PM with 9 crashes in the prior period to 7 PM with 4 crashes in the current period. Overall, most days of the week saw fewer crashes, with Tuesday experiencing the largest reduction from 14 to 6 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The distribution of crash severity remained similar for serious injuries, with 1 serious injury crash in both periods. However, minor injury crashes decreased from 8 to 5, and possible injury crashes decreased from 7 to 4. The proportion of crashes resulting in any injury (serious, minor, or possible) decreased from 29.1% (16 of 55 crashes) to 23.8% (10 of 42 crashes) year-over-year.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.4%
0.0%prior 1
Minor Injury5minor injury crashes11.9%
-37.5%prior 8
Possible Injury4possible injury crashes9.5%
-42.9%prior 7
No Injury32no injury crashes76.2%
-15.8%prior 38

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Followed too closely' saw a substantial count reduction, decreasing from 7 crashes to 2 crashes, a 71.4% decline. 'Failed to yield right of way' also decreased from 7 to 6 crashes, a 14.3% reduction. Conversely, 'Inattention' crashes slightly increased from 6 to 7, representing a 16.7% rise in count.

Officer-Reported Primary Contributing Cause

No improper driving14 (33.3%)-12.5%prior 16
Inattention7 (16.7%)16.7%prior 6
Failed to yield right of way6 (14.3%)-14.3%prior 7
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (7.1%)-40.0%prior 5
Followed too closely2 (4.8%)-71.4%prior 7
Distracted2 (4.8%)
Failure to keep in proper lane or running off road2 (4.8%)
Disregarded traffic signs, signals, road markings1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 40 to 25, aligning with the overall reduction in total crashes. Similarly, crashes on 'Dry' road surfaces decreased from 47 to 35. The number of crashes occurring in 'Dark - lighted roadway' conditions remained stable at 6 for both periods, while crashes in 'Dark - roadway not lighted' decreased from 4 to 3.

Weather

Clear25 (59.5%)
-37.5%prior 40
Cloudy6 (14.3%)
Clear/Clear3 (7.1%)
Clear/Other3 (7.1%)
Rain3 (7.1%)
Rain/Cloudy2 (4.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Weather condition at time of crash

Lighting

Daylight32 (76.2%)
-23.8%prior 42
Dark - lighted roadway6 (14.3%)
0.0%prior 6
Dark - roadway not lighted3 (7.1%)
Dusk1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Lighting condition field

Road Surface

Dry35 (83.3%)
-25.5%prior 47
Wet7 (16.7%)
-12.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 101 to 73 year-over-year. Toyota vehicles involved in crashes decreased from 23 to 12, while Honda vehicles increased from 8 to 12, and Ford vehicles increased from 11 to 12. Among persons involved, the 35-44 age group experienced a significant decrease from 22 to 8 persons, while the 21-25 age group saw an increase from 5 to 8 persons.

Top Vehicle Makes (73 vehicles)

1
TOYOTA12 (16.4%)
-47.8%prior 23
2
HONDA12 (16.4%)
50.0%prior 8
3
FORD12 (16.4%)
9.1%prior 11
4
CHEVROLET5 (6.8%)
-16.7%prior 6
5
KIA5 (6.8%)
-16.7%prior 6
6
HYUNDAI4 (5.5%)
7
VOLKSWAGEN3 (4.1%)
8
GMC2 (2.7%)
9
MAZDA2 (2.7%)
10
JEEP2 (2.7%)
-66.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Vehicle unit records

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

Sex Distribution (81 persons with recorded sex)

Male51 (63.0%)
-21.5%prior 65
Female30 (37.0%)
-42.3%prior 52

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 35 mph speed zone decreased notably from 14 to 7 incidents. Crashes at 30 mph also saw a reduction, from 12 to 10. Conversely, crashes at 45 mph increased from 3 to 4, and at 55 mph, they increased from 3 to 4. No fatalities were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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: 2025-09-01 through 2025-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-09-01 through 2025-09-30 (30 days)
  • Geographic scope: YARMOUTH, MA
  • Total crash records analyzed: 42
  • Total persons involved: 90
  • Total vehicles involved: 73

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: September 2025." Published June 21, 2026. Reporting period: 2025-09-01 to 2025-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/yarmouth/september-2025-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 — September 2025 | ThatCarHitMe.com