Monthly Traffic Safety Analysis

21 CRASHES IN
PEMBROKE, MA
SEPTEMBER 2025

All metrics benchmarked againstSeptember 2024

Total crashes in PEMBROKE, MA increased by 75% year-over-year, rising from 12 in September 2024 to 21 in September 2025. This significant increase in overall crash volume is the most notable shift, accompanied by the emergence of speeding and hit-and-run incidents which were absent in the prior period. Despite the rise in crash numbers, total injuries remained consistent at 2 for both periods.

21

75.0%was 12

Total Crash Events

0

Persons Killed

2

Persons Injured

1

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 substantial increase in crash activity, with total crashes rising by 75% from 12 in September 2024 to 21 in September 2025. Fatalities remained at zero in both periods, and the total number of injured persons held steady at 2 year-over-year.

1

Hit-and-Run Crashes — September 2025

4.8% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 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 Wednesday with 3 crashes in September 2024 to Friday with 5 crashes in September 2025. Similarly, the peak hour for crashes shifted from 7 p.m. to 6 p.m., both recording 3 crashes. Overall, crashes on Fridays saw a notable increase from 2 to 5, while crashes on Wednesdays decreased from 3 to 1.

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

There were no fatal crashes reported in either September 2024 or September 2025. Total injuries remained constant at 2 across both periods, although the proportion of crashes resulting in injuries decreased from 16.7% in September 2024 to 9.5% in September 2025. The severity of reported injuries also shifted from 'Minor Injury' in the prior period to 'Possible Injury' in the current period for the 2 injured persons.

Outcome by Severity (Crash Events)

Possible Injury2possible injury crashes9.5%
No Injury19no injury crashes90.5%
90.0%prior 10

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 count of 'No improper driving' incidents increased by 4, from 4 in September 2024 to 8 in September 2025, maintaining its position as the most frequent contributing factor. 'Inattention' crashes also rose by 1, from 2 to 3, while 'Followed too closely' remained constant with 2 crashes in both periods. Additionally, 'Distracted' and 'Made an improper turn' emerged as new contributing factors in September 2025, each accounting for 2 crashes.

Officer-Reported Primary Contributing Cause

No improper driving8 (38.1%)
Inattention3 (14.3%)
Distracted2 (9.5%)
Followed too closely2 (9.5%)
Made an improper turn2 (9.5%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (4.8%)
Driving too fast for conditions1 (4.8%)
Physical impairment1 (4.8%)
Failure to keep in proper lane or running off road1 (4.8%)

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 increased by 2, from 11 to 13, and 'Cloudy' conditions increased by 2, from 1 to 3. The number of crashes during 'Daylight' hours significantly rose by 7, from 8 to 15. Furthermore, crashes on 'Dry' road surfaces increased by 5, from 11 to 16, while 'Wet' road conditions, absent in the prior period, were associated with 5 crashes in September 2025.

Weather

Clear13 (61.9%)
18.2%prior 11
Cloudy3 (14.3%)
Clear/Clear2 (9.5%)
Rain2 (9.5%)
Fog, smog, smoke1 (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

Daylight15 (71.4%)
87.5%prior 8
Dusk3 (14.3%)
Dark - lighted roadway1 (4.8%)
Dark - roadway not lighted1 (4.8%)
Dark - unknown roadway lighting1 (4.8%)

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

Road Surface

Dry16 (76.2%)
45.5%prior 11
Wet5 (23.8%)

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 (41 vehicles)

1
FORD7 (17.1%)
2
CHEVROLET6 (14.6%)
3
TOYOTA5 (12.2%)
4
RAM3 (7.3%)
5
JEEP2 (4.9%)
6
NISSAN2 (4.9%)
7
HYUNDAI2 (4.9%)
8
HONDA2 (4.9%)
9
VOLKSWAGEN1 (2.4%)
10
VOLVO1 (2.4%)

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

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

Sex Distribution (43 persons with recorded sex)

Male24 (55.8%)
71.4%prior 14
Female19 (44.2%)
72.7%prior 11

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 35 mph speed zones saw a substantial increase of 7, rising from 3 in September 2024 to 10 in September 2025. Conversely, crashes in 40 mph speed zones decreased by 5, from 5 to 0. There was also a slight increase of 1 crash in 45 mph zones, moving from 2 to 3.

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: PEMBROKE, MA
  • Total crash records analyzed: 21
  • Total persons involved: 47
  • Total vehicles involved: 41

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). "PEMBROKE, 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/pembroke/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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Pembroke, MA Crash Report — September 2025 | ThatCarHitMe.com