ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · ROCKPORT, MA · 2024
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/rockport/2024-annual-report
Yearly Traffic Safety Analysis
54 CRASHES IN
ROCKPORT, MA
2024
In 2024, Rockport recorded 54 total crashes, a 5.9% increase from the 51 crashes reported in 2023. While overall crashes rose slightly, the most notable year-over-year change was the elimination of fatal crashes, which dropped from one in the prior period to zero in the current period. The total number of people injured increased from 12 to 15.
54
▲ 5.9%was 51
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
15
▲ 25.0%was 12
Persons Injured
2
▼ -60.0%was 5
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. 3 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash totals in Rockport saw a slight increase year-over-year, rising by 3 incidents from 51 in 2023 to 54 in 2024, representing a 5.9% increase. While total crashes rose, fatal crashes decreased from one to zero. The number of persons injured increased by 25%, from 12 in the prior period to 15 in the current period.
2
Hit-and-Run Crashes — 2024
▼ -60.0% vs prior (5)
Hit-and-run incidents decreased significantly between the two periods. The total count of hit-and-run crashes fell from 5 in 2023 to 2 in 2024, a 60% reduction. Consequently, the hit-and-run rate as a percentage of all crashes dropped from 9.8% to 3.7%.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
2
Pedestrians Injured
1
Cyclists Injured
12
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted year-over-year, with the peak day for collisions moving from Thursday (10 crashes) in 2023 to Wednesday and Saturday (9 crashes each) in 2024. A more pronounced change occurred in the peak hour, which shifted from an afternoon peak at 2 p.m. in the prior year to a distinct morning peak at 9 a.m. (9 crashes) in the current year. The summer crash concentration also increased, with July 2024 seeing 14 crashes compared to the prior year's peak of 8 crashes in June.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity improved with the elimination of fatal crashes, which dropped from one in 2023 to zero in 2024. The count of serious injury crashes remained stable at one incident in both periods. However, crashes resulting in minor or possible injuries increased; minor injury crashes rose from 7 to 8, and possible injury crashes doubled from 2 to 4.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
A comparison of contributing factors reveals a significant rise in crashes attributed to inattention, with the count more than doubling from 5 in 2023 to 11 in 2024, a 120% increase in count. Similarly, crashes involving 'Failure to keep in proper lane' increased from 1 to 5. Conversely, crashes involving erratic driving decreased from 4 to 3, and those related to fatigue dropped from 3 to 1.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The proportion of crashes occurring on dry road surfaces increased from 64.7% (33 crashes) in 2023 to 79.6% (43 crashes) in 2024. Correspondingly, crashes on wet surfaces decreased from 15 incidents to 7. Crashes under clear weather conditions also formed a larger share of the total, rising from 49% of all incidents in the prior year to 66.7% in the current year. Lighting conditions remained largely consistent across both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The vehicle makes involved in crashes showed some shifts; Toyota's involvement nearly doubled from 8 vehicles in 2023 to 15 in 2024, making it the most common make in the current period. Conversely, Chevrolet, the most frequent make in the prior year with 11 vehicles, was involved in only 3 crashes in 2024. Regarding persons involved, there was a notable increase in the 55-64 age group (from 10 to 19 people) and the 65+ age group (from 27 to 35 people).
Top Vehicle Makes (94 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
14 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (107 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones remained broadly similar year-over-year, with most incidents occurring in 25 MPH zones in both periods (22 in 2023, 25 in 2024). The number of crashes in 30 MPH zones was unchanged at 8 incidents. However, the single fatal crash from 2023, which occurred in a 30 MPH zone, was not repeated in 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: ROCKPORT, MA
- Total crash records analyzed: 54
- Total persons involved: 121
- Total vehicles involved: 94
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). "ROCKPORT, MA Crash Intelligence Report: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/rockport/2024-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: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved