Monthly Traffic Safety Analysis

14 CRASHES IN
DUXBURY, MA
SEPTEMBER 2025

All metrics benchmarked againstSeptember 2024

In September 2025, Duxbury recorded 14 crashes, a 6.7% decrease from the 15 crashes reported in September 2024. The most significant year-over-year shift was the absence of fatalities in the current period, down from one fatality in the prior year.

14

-6.7%was 15

Total Crash Events

0

-100.0%was 1

Persons Killed

2

-71.4%was 7

Persons Injured

0

-100.0%was 1

Fatal Crash Events

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

Overall crash activity in Duxbury shows a downward trend year-over-year, with total crashes decreasing by 6.7% from 15 to 14. This decline was accompanied by a substantial reduction in total injuries, which fell from 7 to 2, and the elimination of crash fatalities, down from 1 in the prior period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1-100.0%

2

Motorists Injured

Prior: 7-71.4%

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 temporal distribution of crashes shifted year-over-year, with the peak day moving from Sunday in September 2024 (4 crashes) to Friday in September 2025 (4 crashes). Similarly, the peak crash hour changed from 11 AM (3 crashes) in the prior period to 7 PM (2 crashes) in the current period.

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

Duxbury experienced a notable improvement in crash severity year-over-year, with no fatalities reported in September 2025 compared to one fatality in September 2024. Total injuries also decreased significantly from 7 in the prior period to 2 in the current period, marking a positive trend in crash outcomes.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes7.1%
0.0%prior 1
Minor Injury1minor injury crashes7.1%
-50.0%prior 2
No Injury12no injury crashes85.7%
33.3%prior 9

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

The contributing factors to crashes saw shifts, with 'No improper driving' increasing by 2 crashes from 3 to 5 year-over-year. Conversely, 'Inattention' decreased by 2 crashes, falling from 3 to 1. 'Failed to yield right of way' emerged as a contributing factor in 3 crashes in the current period, while it was not among the top factors in the prior period.

Officer-Reported Primary Contributing Cause

No improper driving5 (35.7%)
Failed to yield right of way3 (21.4%)
Followed too closely2 (14.3%)
Exceeded authorized speed limit1 (7.1%)
Inattention1 (7.1%)
Failure to keep in proper lane or running off road1 (7.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (7.1%)

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 under clear weather conditions decreased slightly from 11 in September 2024 to 10 in September 2025, while crashes during rainy conditions were observed in the current period. Crashes occurring in daylight decreased from 10 to 9, and crashes in dark but lighted roadways increased from 1 to 2. Data for road surface conditions was not available for the prior period.

Weather

Clear10 (71.4%)
-9.1%prior 11
Rain/Rain2 (14.3%)
Cloudy1 (7.1%)
Rain/Clear1 (7.1%)

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

Lighting

Daylight9 (64.3%)
-10.0%prior 10
Dark - lighted roadway2 (14.3%)
Dark - roadway not lighted2 (14.3%)
Dusk1 (7.1%)

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

Road Surface

Dry10 (71.4%)
Wet4 (28.6%)

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

Vehicles & Demographics

Top Vehicle Makes (23 vehicles)

1
TOYOTA7 (30.4%)
2
SUBARU4 (17.4%)
3
HYUNDAI2 (8.7%)
4
KIA1 (4.3%)
5
LEXUS1 (4.3%)
6
LNDR1 (4.3%)
7
MACK1 (4.3%)
8
MAZDA1 (4.3%)
9
MERCEDES-BENZ1 (4.3%)
10
FORD1 (4.3%)

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

Sex Distribution (32 persons with recorded sex)

Female17 (53.1%)
41.7%prior 12
Male15 (46.9%)
-11.8%prior 17

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

Crash distribution across speed zones showed changes, with crashes in the 25 mph zone decreasing from 2 to 1 and in the 60 mph zone decreasing from 6 to 3. Conversely, crashes in the 30 mph zone increased from 3 to 5. New crash occurrences were noted in 20, 40, and 45 mph zones in the current period, which did not feature in the prior period's data.

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: DUXBURY, MA
  • Total crash records analyzed: 14
  • Total persons involved: 32
  • Total vehicles involved: 23

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). "DUXBURY, 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/duxbury/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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Duxbury, MA Crash Report — September 2025 | ThatCarHitMe.com