Monthly Traffic Safety Analysis

22 CRASHES IN
ROCKLAND, MA
SEPTEMBER 2025

All metrics benchmarked againstSeptember 2024

In Rockland, September 2025 saw a decrease in total crashes compared to September 2024, with 22 crashes versus 26, representing a 15.38% reduction. However, a notable shift occurred with the presence of 1 fatality in September 2025, whereas no fatalities were recorded in the prior year.

22

▼ -15.4%was 26

Total Crash Events

1

Persons Killed

6

▼ -40.0%was 10

Persons Injured

1

▼ -75.0%was 4

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.

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 incidents in Rockland decreased year-over-year, with total crashes falling from 26 in September 2024 to 22 in September 2025. Despite this reduction in total incidents, total fatalities increased from 0 to 1, while total injuries decreased from 10 to 6.

1

Hit-and-Run Crashes — September 2025

▼ -75.0% vs prior (4)

Hit-and-run incidents significantly decreased year-over-year, falling from 4 crashes in September 2024 to 1 crash in September 2025. Consequently, the hit-and-run rate decreased from 15.4% to 4.5% during this period.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0→%

6

Motorists Injured

Prior: 8↓-25.0%

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 temporal distribution of crashes shifted year-over-year; Mondays became the peak day for crashes in September 2025 with 5 incidents, compared to Fridays in September 2024 which also had 5 incidents. The peak hour for crashes moved from 3 PM in September 2024 to 7 PM in September 2025, with both periods recording 3 crashes during their respective peak hours.

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 severity profile changed significantly, with the fatal crash rate increasing from 0% in September 2024 to 4.55% in September 2025 due to one fatal crash. Minor Injury crashes (code B) decreased from 8 (30.8% share) to 3 (13.6% share), while 'No Injury' crashes increased from 15 (57.7% share) to 16 (72.7% share).

Outcome by Severity (Crash Events)

Fatal1fatal crashes4.5%
Minor Injury3minor injury crashes13.6%
↓-62.5%prior 8
Possible Injury2possible injury crashes9.1%
→0.0%prior 2
No Injury16no injury crashes72.7%
↑6.7%prior 15

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

Contributing factors saw shifts, with 'Inattention' increasing from 4 crashes in September 2024 to 7 crashes in September 2025, representing a 75% increase in count. Conversely, 'Failed to yield right of way' decreased from 4 crashes to 1 crash, a 75% decrease in count. 'Followed too closely' also saw a decrease, from 4 crashes to 3 crashes.

Officer-Reported Primary Contributing Cause

Inattention7 (31.8%)
No improper driving4 (18.2%)
Followed too closely3 (13.6%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (9.1%)
History heart/epilepsy/fainting2 (9.1%)
Failure to keep in proper lane or running off road1 (4.5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (4.5%)
Other improper action1 (4.5%)
Failed to yield right of way1 (4.5%)

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

Regarding conditions, crashes occurring in 'Clear' weather decreased from 20 in September 2024 to 14 in September 2025. Crashes during 'Daylight' conditions also decreased from 19 to 14. However, crashes in 'Dark - lighted roadway' conditions increased from 3 to 5.

Weather

Clear14 (63.6%)
↓-30.0%prior 20
Rain3 (13.6%)
Clear/Clear2 (9.1%)
Cloudy1 (4.5%)
Cloudy/Rain1 (4.5%)
Rain/Cloudy1 (4.5%)

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

Lighting

Daylight14 (63.6%)
↓-26.3%prior 19
Dark - lighted roadway5 (22.7%)
Dusk2 (9.1%)
Dark - roadway not lighted1 (4.5%)

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

Road Surface

Dry17 (77.3%)
↓-19.0%prior 21
Wet5 (22.7%)
→0.0%prior 5

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 (39 vehicles)

1
JEEP5 (12.8%)
2
FORD3 (7.7%)
↓-40.0%prior 5
3
CHEVROLET3 (7.7%)
↓-40.0%prior 5
4
TOYOTA3 (7.7%)
↓-75.0%prior 12
5
HONDA3 (7.7%)
6
RAM3 (7.7%)
7
NISSAN2 (5.1%)
8
HYUNDAI2 (5.1%)
9
VOLKSWAGEN2 (5.1%)
10
PORS1 (2.6%)

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

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

Sex Distribution (42 persons with recorded sex)

Male28 (66.7%)
↓-9.7%prior 31
Female14 (33.3%)
↓-36.4%prior 22

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

The distribution of crashes by speed limit zones shifted, with crashes in 35 mph zones increasing from 8 in September 2024 to 12 in September 2025. This 35 mph zone also accounted for the single fatal crash in the current period, whereas no fatalities were recorded in this zone in the prior period. Crashes in 25 mph zones decreased from 5 to 2, and in 30 mph zones from 7 to 4.

Fatal crashes by zone: 35 mph: 1 of 12 (8.333%)

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: ROCKLAND, MA
  • Total crash records analyzed: 22
  • Total persons involved: 47
  • Total vehicles involved: 39

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). "ROCKLAND, 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/rockland/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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Rockland, MA Crash Report — September 2025 | ThatCarHitMe.com