Monthly Traffic Safety Analysis

4 CRASHES IN
WEST NEWBURY, MA
SEPTEMBER 2025

All metrics benchmarked againstSeptember 2024

In WEST NEWBURY, total crashes in September 2025 were 4, a substantial increase from the 1 crash reported in September 2024. This represents a 300% year-over-year increase in overall crash incidents. The most notable shift was the rise in total crashes, alongside a decrease in total injuries from 1 to 0.

4

300.0%was 1

Total Crash Events

0

Persons Killed

0

-100.0%was 1

Persons Injured

1

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. 4 crashes with unreported severity are not shown in the severity breakdown.

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

The overall trend indicates a significant increase in crash incidents year-over-year, with total crashes rising from 1 in September 2024 to 4 in September 2025. This represents a 300% increase in crash volume. Despite the rise in crashes, total injuries decreased from 1 to 0.

1

Hit-and-Run Crashes — September 2025

25.0% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

When Crashes Happen

The peak day for crashes shifted from Tuesday in September 2024 to Friday (with 1 crash) in September 2025, though Tuesday, Wednesday, and Thursday also recorded 1 crash each in the current period. The peak hour for crashes also shifted from 4 PM in September 2024 to 7 PM in September 2025, with other hours like 7 AM, 12 PM, and 3 PM also recording 1 crash each in the current period. The prior period had only one crash, limiting detailed pattern comparison.

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)

Top Contributing Factors

Officer-Reported Primary Contributing Cause

Failure to keep in proper lane or running off road1 (25%)
Inattention1 (25%)
No improper driving1 (25%)

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

Weather

Clear3 (75.0%)
Cloudy/Rain1 (25.0%)

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

Lighting

Daylight3 (75.0%)
Dark - lighted roadway1 (25.0%)

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

Road Surface

Dry3 (75.0%)
Wet1 (25.0%)

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 (6 vehicles)

1
CADI1 (16.7%)
2
MAZDA1 (16.7%)
3
RAM1 (16.7%)
4
SUBARU1 (16.7%)
5
TOYOTA1 (16.7%)

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

Sex Distribution (6 persons with recorded sex)

Male4 (66.7%)
100.0%prior 2
Female2 (33.3%)
0.0%prior 2

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

In September 2024, the single crash occurred in a 30 mph speed zone. In September 2025, one crash occurred in a 30 mph speed zone, and three crashes occurred in 40 mph speed zones. This indicates a shift with a majority of crashes occurring in 40 mph zones in the current period, compared to only 30 mph zones in the prior period. Neither period recorded any fatal crashes in any speed zone.

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: WEST NEWBURY, MA
  • Total crash records analyzed: 4
  • Total persons involved: 6
  • Total vehicles involved: 6

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: 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/west-newbury/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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West Newbury, MA Crash Report — September 2025 | ThatCarHitMe.com