ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WEST NEWBURY, 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/west-newbury/2025-annual-report
Yearly Traffic Safety Analysis
40 CRASHES IN
WEST NEWBURY, MA
2025
In 2025, West Newbury recorded 40 total traffic crashes, an 18.4% decrease from the 49 crashes reported in 2024. Total injuries also saw a slight decline from 7 to 6, while fatalities remained at zero for both periods. The most significant year-over-year shift was a 75% reduction in hit-and-run incidents, which fell from 4 crashes in 2024 to 1 in 2025.
40
▼ -18.4%was 49
Total Crash Events
0
Persons Killed
6
▼ -14.3%was 7
Persons Injured
1
▼ -75.0%was 4
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. 1 crash with unreported severity is 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 safety metrics in West Newbury showed a positive trend year-over-year. The total number of crashes fell by 18.4%, from 49 in 2024 to 40 in 2025. This downward trend was also reflected in the number of persons injured, which decreased from 7 to 6, while no fatalities were recorded in either period.
1
Hit-and-Run Crashes — 2025
▼ -75.0% vs prior (4)
Hit-and-run incidents decreased significantly year-over-year. In 2025, there was only 1 hit-and-run crash recorded, representing a 75% reduction from the 4 incidents in 2024. As a result, the hit-and-run rate, which measures the percentage of all crashes involving a driver leaving the scene, fell from 8.2% in 2024 to 2.5% in 2025.
Vulnerable Road User Casualties
0
Motorists Killed
6
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 timing of crashes shifted between the two periods. The peak day for collisions moved from Friday (12 crashes) in 2024 to Wednesday (12 crashes) in 2025. Similarly, the peak hour for crashes shifted from the morning commute at 8 a.m. in 2024 (6 crashes) to the evening commute in 2025, when 6 p.m. was a peak time with 5 crashes.
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
Crash severity improved in 2025, with no fatal or serious injury crashes recorded, compared to one serious injury crash in 2024. The total number of persons injured decreased slightly from 7 to 6. The proportion of crashes resulting in any injury (minor or possible) also declined, from 14.3% of all crashes in 2024 to 12.5% in 2025.
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 leading contributing factors remained consistent, with 'No improper driving' and 'Inattention' being the top two cited causes in both years. The count of crashes attributed to 'No improper driving' decreased from 24 to 19, while incidents involving 'Inattention' held steady at 7. Crashes involving an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' were halved, dropping from a count of 4 in 2024 to 2 in 2025. Although the count for inattention-related crashes was unchanged, its share of all crashes increased from 14.3% to 17.5%.
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
In both years, most crashes occurred in daylight on dry roads. However, the proportion of crashes in daylight decreased from 67.3% in 2024 to 62.5% in 2025. While the absolute number of crashes on adverse road surfaces (wet, snow, slush) was nearly identical (9 in 2024 vs. 8 in 2025), their share of total crashes increased from 18.4% to 20%. A similar trend was observed for crashes in adverse weather, which accounted for a larger share of incidents in 2025 (20%) compared to 2024 (16.3%).
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 makes of vehicles most frequently involved in crashes shifted year-over-year. In 2024, Toyota and Ford led with 10 vehicles each, but in 2025, Subaru and Toyota were the most common makes, each involved in 7 crashes. Regarding the age of persons involved, the 35-44 age group's representation grew from 8.1% of all individuals in 2024 to 18.3% in 2025. In contrast, the proportion of persons in the 16-20 age group decreased from 19.8% to 16.7%.
Top Vehicle Makes (56 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
2 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (57 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
The distribution of crashes across speed zones changed between periods, though no fatalities occurred in any zone in either year. There was a significant decrease in crashes within 35 mph zones, which fell from 17 incidents in 2024 to 7 in 2025. Crashes in 40 mph zones also decreased from 14 to 9. Conversely, 2025 saw the emergence of 3 crashes in 65 mph zones, a speed limit category that had zero crashes in the prior year.
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: WEST NEWBURY, MA
- Total crash records analyzed: 40
- Total persons involved: 60
- Total vehicles involved: 56
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). "WEST NEWBURY, 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/west-newbury/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