ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BELLINGHAM, MA · NOVEMBER 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/bellingham/november-2025-report
Monthly Traffic Safety Analysis
47 CRASHES IN
BELLINGHAM, MA
NOVEMBER 2025
In November 2025, Bellingham experienced 47 total crashes, an increase of 9.3% compared to the 43 crashes recorded in November 2024. A significant shift was observed in fatalities, which decreased from one in the prior period to zero in the current period. Conversely, hit-and-run crashes increased from zero in the prior period to three in the current period.
47
▲ 9.3%was 43
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
17
▲ 13.3%was 15
Persons Injured
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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in Bellingham increased year-over-year, with total crashes rising by 9.3% from 43 to 47. Injuries also saw an increase, with 17 total injuries in the current period compared to 15 in the prior period, marking a 13.3% rise. However, the most positive trend was the complete elimination of fatalities, which decreased by 100% from one in the prior period to zero in the current period.
3
Hit-and-Run Crashes — November 2025
6.4% hit-and-run rate this period vs 0.0% prior. Prior period: 0.
Vulnerable Road User Casualties
0
Motorists Killed
0
Other Killed
16
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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 moving from Thursday in November 2024 (10 crashes) to Saturday in November 2025 (12 crashes). The peak crash hour also changed, moving from 3 PM with 8 crashes in the prior period to 5 PM with 7 crashes in the current period. Monday also saw a notable increase in crashes, rising from 4 in the prior period to 11 in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The fatal crash rate decreased from 2.3% in November 2024 to 0% in November 2025, with total fatalities dropping from one to zero. While serious injuries remained constant at one in both periods, minor injury crashes decreased from 7 to 4, and possible injury crashes increased from 3 to 6. Overall, the proportion of injury-involved crashes (A, B, C severity) decreased slightly from 27.9% in the prior period to 23.4% in the current period.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'No improper driving' increased by 4 crashes, from 9 in November 2024 to 13 in November 2025. 'Failed to yield right of way' also increased by 3 crashes, rising from 5 to 8. Notably, 'Followed too closely' more than doubled, increasing by 4 crashes from 3 to 7, while 'Inattention' decreased by 3 crashes, from 4 to 1.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions slightly decreased from 34 in November 2024 to 31 in November 2025, while crashes during rain conditions increased from 3 to 8. A significant shift was observed in lighting conditions, with crashes in 'Dark - lighted roadway' more than doubling from 9 to 20. Conversely, crashes during daylight decreased from 26 to 22, and those occurring at dusk fell from 6 to 2.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 80 in November 2024 to 88 in November 2025. Toyota remained the most common vehicle make involved, with its count increasing from 14 to 21, while Chevrolet remained constant at 8. In terms of person demographics, involvement for males increased from 48 to 56, and for females from 39 to 42; the 26-34 age group saw a notable increase in involvement, from 12 to 16 persons.
Top Vehicle Makes (88 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Vehicle unit records
8 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (98 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Person-level records linked to crash events
Speed Limit Zones
There was a shift in crash distribution across speed zones year-over-year, with crashes in the 30 mph zone increasing significantly from 2 to 9, and in the 40 mph zone from 1 to 6. Conversely, crashes in the 35 mph zone decreased from 13 to 8. The single fatality recorded in November 2024 occurred in the 35 mph zone, whereas no fatalities were reported in any speed zone in November 2025.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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: 2025-11-01 through 2025-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-11-01 through 2025-11-30 (30 days)
- Geographic scope: BELLINGHAM, MA
- Total crash records analyzed: 47
- Total persons involved: 106
- Total vehicles involved: 88
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). "BELLINGHAM, MA Crash Intelligence Report: November 2025." Published June 21, 2026. Reporting period: 2025-11-01 to 2025-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/bellingham/november-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-11-01 – 2025-11-30
Generated: June 21, 2026 · All rights reserved