ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEW BEDFORD, 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/new-bedford/november-2025-report
Monthly Traffic Safety Analysis
383 CRASHES IN
NEW BEDFORD, MA
NOVEMBER 2025
In November 2025, New Bedford experienced 383 total crashes, an increase of 21.97% compared to the 314 crashes reported in November 2024. The most notable shift was in fatalities, which rose from 0 in the prior period to 3 in the current period, marking a significant change in crash outcomes.
383
▲ 22.0%was 314
Total Crash Events
3
Persons Killed
107
▲ 52.9%was 70
Persons Injured
59
▲ 37.2%was 43
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 24 crashes with unreported severity are not shown in the severity breakdown.
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, crash data for November indicates a rising trend year-over-year, with total crashes increasing by 21.97% from 314 to 383. This increase was accompanied by a concerning rise in fatalities, from 0 in November 2024 to 3 in November 2025.
59
Hit-and-Run Crashes — November 2025
▲ 37.2% vs prior (43)
The number of hit-and-run crashes increased by 16, rising from 43 in November 2024 to 59 in November 2025. This resulted in an increase in the hit-and-run rate from 13.7% to 15.4% of all crashes year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
3
Motorists Killed
0
Other Killed
4
Pedestrians Injured
101
Motorists Injured
2
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 peak day for crashes shifted from Friday with 57 crashes in November 2024 to Saturday with 80 crashes in November 2025. The peak hour for crashes remained consistent at 5 PM in both periods, increasing slightly from 34 crashes in the prior year to 36 crashes in the current year.
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 current period saw 2 fatal crashes and 3 total fatalities, compared to 0 fatal crashes and 0 fatalities in the prior period. Serious injury crashes increased from 3 (1% of total crashes) to 5 (1.3% of total crashes), while minor injury crashes also rose from 32 (10.2%) to 43 (11.2%) year-over-year.
Severity is per crash event (most severe injury). 2 fatal crash events resulted in 3 persons killed.
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
The number of crashes where 'No improper driving' was cited increased by 23, from 135 to 158. 'Inattention' as a contributing factor saw a count increase of 14, rising from 21 to 35 crashes. Conversely, 'Failed to yield right of way' decreased by 3 crashes, from 19 to 16.
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 under 'Clear' weather conditions increased by 36, from 226 to 262, while 'Cloudy' conditions saw an increase of 27 crashes, from 11 to 38. Crashes on 'Dry' road surfaces increased by 63, from 270 to 333, and crashes during 'Daylight' increased by 35, from 177 to 212.
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 by 142, from 609 to 751. Honda vehicles involved in crashes increased by 30, from 75 to 105, while Toyota saw a smaller increase of 4, from 97 to 101. The 26-34 age group saw a decrease of 28 persons involved in crashes, from 139 to 111, while the 45-54 age group saw an increase of 39 persons, from 64 to 103.
Top Vehicle Makes (751 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Vehicle unit records
194 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (683 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
Crashes in the 30 mph speed zone increased from 194 to 250, with one fatal crash occurring in this zone in the current period compared to none in the prior period. The 65 mph speed zone also saw an increase from 7 to 8 crashes, with one fatal crash reported in this zone in the current period.
Fatal crashes by zone: 30 mph: 1 of 250 (0.4%) · 65 mph: 1 of 8 (12.5%)
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: NEW BEDFORD, MA
- Total crash records analyzed: 383
- Total persons involved: 915
- Total vehicles involved: 751
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). "NEW BEDFORD, 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/new-bedford/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