ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEW BEDFORD, 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/new-bedford/2025-annual-report
Yearly Traffic Safety Analysis
4,006 CRASHES IN
NEW BEDFORD, MA
2025
In 2025, New Bedford recorded 4,006 total crashes, a 16.5% increase from the 3,438 crashes documented in 2024. This rise in incidents was accompanied by a 3.8% increase in total injuries, from 991 to 1,029, and a slight increase in fatalities from 6 to 7. The most notable shift was the overall growth in crash volume, with hit-and-run incidents in particular increasing by over 27% year-over-year.
4,006
▲ 16.5%was 3,438
Total Crash Events
7
▲ 16.7%was 6
Persons Killed
1,029
▲ 3.8%was 991
Persons Injured
652
▲ 27.6%was 511
Hit-and-Run Crashes
Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 275 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
Crash trends in New Bedford show a significant increase year-over-year. Total crashes rose by 16.5%, from 3,438 in 2024 to 4,006 in 2025. While total injuries increased by a more modest 3.8% to 1,029, fatalities also saw a slight rise from 6 to 7 people.
652
Hit-and-Run Crashes — 2025
▲ 27.6% vs prior (511)
Hit-and-run incidents increased significantly year-over-year in both absolute numbers and as a proportion of total crashes. The count of hit-and-run crashes rose by 27.6%, from 511 in 2024 to 652 in 2025. This corresponds to an increase in the hit-and-run rate, which climbed from 14.9% of all crashes in the prior year to 16.3% in the current year.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
6
Motorists Killed
0
Other Killed
54
Pedestrians Injured
34
Cyclists Injured
926
Motorists Injured
15
Other 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
Temporal patterns show a general intensification of crash activity year-over-year. While Friday remained the peak day for crashes in both 2024 (541 crashes) and 2025 (642 crashes), the peak hour shifted slightly later from 2 p.m. in the prior year to 3 p.m. in the current year. Crash counts increased across all days of the week, with the afternoon hours from 2 p.m. to 5 p.m. experiencing a notable rise in incidents.
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
The severity of crashes shifted slightly towards less severe outcomes despite an increase in total incidents. The fatal crash rate remained stable at 0.15% in both 2024 and 2025, though the absolute number of fatal crashes rose from 5 to 6. The proportion of crashes resulting in any level of injury decreased from 21.1% in 2024 to 18.5% in 2025, while the share of non-injury crashes increased from 71.1% to 74.5%.
Severity is per crash event (most severe injury). 6 fatal crash events resulted in 7 persons killed.
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 year-over-year, though their counts varied. 'No improper driving' was the most cited factor in both periods, with its count increasing by 36.4% from 1,309 in 2024 to 1,785 in 2025. Conversely, crashes attributed to 'Inattention' decreased in count by 7.3% (from 301 to 279), and those involving 'Failed to yield right of way' dropped by 9.6% (from 240 to 217). Crashes involving 'Disregarded traffic signs, signals, road markings' saw a 23.5% increase in count, rising from 85 to 105.
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 majority of crashes in both periods occurred in clear weather and on dry roads. In 2025, 84.0% of crashes happened on dry surfaces, a slight increase from 83.0% in 2024, while the proportion of crashes on wet surfaces decreased from 14.2% to 11.5%. Crashes during daylight hours accounted for a slightly larger share of the total, rising from 65.7% in 2024 to 67.9% in 2025. The proportion of crashes occurring in clear weather remained stable at approximately 70% for both years.
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 top three vehicle makes involved in crashes remained Toyota, Honda, and Ford in both 2024 and 2025, with all three seeing an increase in total incidents. Toyota-involved crashes increased from 1,069 to 1,195, and Ford-involved crashes rose from 658 to 804. An analysis of persons involved shows a shift in age demographics, with the proportion of individuals in the 35-44 age group increasing from 13.2% to 14.4% and the 55-64 age group increasing from 7.8% to 8.9% year-over-year.
Top Vehicle Makes (7,996 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
2,115 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (7,255 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
Crashes predominantly occurred in 30 mph speed zones in both years, and this concentration increased in 2025. The number of crashes in 30 mph zones rose from 1,963 to 2,420, and their share of all recorded crashes grew from 57.1% to 60.4%. Fatal crashes also shifted within zones; four occurred in 30 mph zones in 2025 compared to three in 2024, while a new fatal crash was recorded in a 65 mph zone.
Fatal crashes by zone: 30 mph: 4 of 2,420 (0.165%) · 35 mph: 1 of 174 (0.575%) · 65 mph: 1 of 96 (1.042%)
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: NEW BEDFORD, MA
- Total crash records analyzed: 4,006
- Total persons involved: 9,610
- Total vehicles involved: 7,996
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: 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/new-bedford/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