ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · 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/newbury/2025-annual-report
Yearly Traffic Safety Analysis
103 CRASHES IN
NEWBURY, MA
2025
In Newbury, total traffic crashes increased by 24.1% from 83 in 2024 to 103 in 2025. While the overall number of crashes and injuries rose, the most notable change was a positive one: the number of traffic fatalities dropped from two in the prior year to zero in the current year.
103
▲ 24.1%was 83
Total Crash Events
0
▼ -100.0%was 2
Persons Killed
23
▲ 21.1%was 19
Persons Injured
4
▲ 33.3%was 3
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. 2 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
The overall trend in traffic incidents shows an increase year-over-year. Total crashes rose from 83 to 103, an increase of 24.1%. Similarly, the number of persons injured in these crashes grew from 19 to 23, a 21.1% rise compared to the previous year.
4
Hit-and-Run Crashes — 2025
▲ 33.3% vs prior (3)
Hit-and-run incidents saw a slight increase year-over-year. The absolute count of hit-and-run crashes rose from three to four. This resulted in a marginal increase in the hit-and-run rate, which climbed from 3.6% of all crashes in the prior period to 3.9% in the current period.
Vulnerable Road User Casualties
0
Motorists Killed
23
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 peak day for crashes remained Saturday in both periods, with the count increasing from 18 to 20. However, the peak hour for collisions shifted slightly from the 4 p.m. hour in 2024 (11 crashes) to the 3 p.m. and 5 p.m. hours in 2025, which each recorded 11 crashes. Mondays also saw a significant increase in crash activity, rising from 8 incidents in the prior year to 18 in the current year.
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
A significant improvement in crash severity was observed, with fatal crashes decreasing from two in 2024 to zero in 2025. While the number of serious injury crashes increased from one to three, the share of crashes involving minor injuries decreased from 18.1% to 12.6%. Consequently, the proportion of crashes resulting in no injuries increased from 75.9% to 81.6% of all incidents.
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
While "No improper driving" remained the most frequent circumstance in both periods, its count increased from 31 to 36 crashes. The count for crashes involving "Driving too fast for conditions" held steady at 8 incidents. Notably, crashes attributed to "Inattention" doubled in count from 3 to 6, while those related to "Failure to keep in proper lane or running off road" decreased from 7 incidents to 3.
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 in daylight was stable, but incidents in dark conditions increased from 25 to 41, raising their share of total crashes from 30.1% to 39.8%. There was a significant shift in road surface conditions, with crashes on wet roads increasing from 5 to 21. Conversely, crashes on snowy surfaces decreased from 15 in the prior year to 5 in the current year.
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
Toyota, Honda, and Ford were the top three vehicle makes involved in crashes in both years, with the count for each increasing. A notable demographic shift occurred among persons involved in crashes; the 65+ age group became the most represented cohort with 35 individuals, more than doubling from 15 in the prior year. This displaced the 35-44 age group, which was the largest in the previous period with 25 individuals.
Top Vehicle Makes (153 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
17 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (172 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
There was a shift in where crashes occurred, with 30 mph zones seeing the highest number of incidents (24) in the current year, a sharp increase from 8 in the prior year. Crashes in 65 mph zones, which were the most common location in the prior year with 24 incidents, decreased to 20. Importantly, the two fatal crashes from the prior period both occurred in a 65 mph zone, whereas no fatal crashes were recorded in any speed zone in the current 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: NEWBURY, MA
- Total crash records analyzed: 103
- Total persons involved: 187
- Total vehicles involved: 153
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). "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/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