ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · ROCKLAND, MA · 2025
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/rockland/2025-annual-report
Yearly Traffic Safety Analysis
241 CRASHES IN
ROCKLAND, MA
2025
In 2025, Rockland recorded 241 total crashes, a 15.7% decrease from the 286 crashes reported in 2024. Despite the overall reduction in collisions, the most significant year-over-year change was the occurrence of two fatal crashes in 2025, whereas no fatalities were recorded in the previous year.
241
▼ -15.7%was 286
Total Crash Events
2
Persons Killed
85
▼ -30.3%was 122
Persons Injured
15
▲ 25.0%was 12
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 5 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 Rockland decreased by 15.7% from 286 in 2024 to 241 in 2025. This downward trend was also reflected in the number of injuries, which fell by 30.3% from 122 to 85. However, the number of fatalities increased from zero in the prior period to two in the current period.
15
Hit-and-Run Crashes — 2025
▲ 25.0% vs prior (12)
The number of hit-and-run incidents increased from 12 in 2024 to 15 in 2025. This represents a rise in the hit-and-run rate, which grew from 4.2% of all crashes in the prior period to 6.2% in the current period. The data indicates an upward trend in both the absolute count and the proportional rate of hit-and-run crashes.
Vulnerable Road User Casualties
2
Motorists Killed
85
Motorists Injured
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 showed notable shifts between the two periods. The peak day for collisions moved from Friday (55 crashes) in 2024 to Tuesday (47 crashes) in 2025. Similarly, the peak hour for crashes shifted one hour earlier, from 4 p.m. in the prior year to 3 p.m. in the current year, which saw 30 incidents during that hour.
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, crash severity saw a significant change with the introduction of two fatal incidents in 2025, resulting in a fatal crash rate of 0.83 per 100 crashes, up from zero in 2024. The proportion of crashes resulting in any level of injury (Serious, Minor, or Possible) decreased from 31.8% of all crashes in 2024 to 24.5% in 2025. Consequently, the share of crashes with no reported injuries increased from 66.8% to 72.6% year-over-year.
Outcome by Severity (Crash Events)
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 primary contributing factors cited in crashes remained consistent year-over-year, with 'Failed to yield right of way' and 'Inattention' being the top two driver-related actions in both periods. The count of crashes attributed to failing to yield decreased from 47 to 43, while those involving inattention fell from 43 to 41. The number of crashes due to 'Followed too closely' and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' remained unchanged, with 27 and 16 incidents respectively in both 2024 and 2025.
Officer-Reported Primary Contributing Cause
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 proportion of crashes occurring on dry roads decreased from 81.5% in 2024 to 75.5% in 2025, with a corresponding increase in the share of crashes on wet surfaces from 17.1% to 19.5%. Crashes during daylight hours constituted a larger share of the total, rising from 61.9% to 68.5% year-over-year. While collisions in clear weather conditions decreased in absolute terms, their share of the total also fell from 74.1% to 59.8%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained Toyota, Ford, and Honda, though their order shifted. In 2025, Ford (54 vehicles) surpassed Honda (45 vehicles) for the second position, while Toyota remained the most common make despite its count decreasing from 89 to 69 vehicles. An analysis of persons involved shows a notable decrease in the 35-44 age group, which fell from 119 individuals in 2024 to 69 in 2025. Conversely, the number of persons in the 16-20 age group increased slightly from 67 to 71.
Top Vehicle Makes (450 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
40 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (491 persons with recorded sex)
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 30 mph and 35 mph speed zones in both years. The number of incidents in 30 mph zones decreased from 112 to 94, while collisions in 60 mph zones were halved, dropping from 34 to 17. The two fatal crashes recorded in 2025 occurred in 30 mph and 35 mph zones, whereas no fatal crashes were recorded in any speed zone in the prior year.
Fatal crashes by zone: 30 mph: 1 of 94 (1.064%) · 35 mph: 1 of 75 (1.333%)
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: ROCKLAND, MA
- Total crash records analyzed: 241
- Total persons involved: 539
- Total vehicles involved: 450
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: 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/rockland/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved