ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEW BEDFORD, MA · DECEMBER 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/december-2025-report
Monthly Traffic Safety Analysis
391 CRASHES IN
NEW BEDFORD, MA
DECEMBER 2025
In December 2025, NEW BEDFORD, MA experienced 391 crashes, an increase of 19.6% compared to the 327 crashes recorded in December 2024. Despite the rise in total crashes, total injuries saw a significant decrease of 31%, from 100 injuries in December 2024 to 69 injuries in December 2025. This indicates a trend of more crashes with fewer resulting injuries year-over-year.
391
▲ 19.6%was 327
Total Crash Events
0
Persons Killed
69
▼ -31.0%was 100
Persons Injured
62
▲ 34.8%was 46
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. 27 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, total crashes in NEW BEDFORD, MA are trending upwards year-over-year, increasing by 64 incidents, or 19.6%, from 327 crashes in December 2024 to 391 crashes in December 2025. This rise in crash volume is observed alongside a notable decrease in the number of injuries reported.
62
Hit-and-Run Crashes — December 2025
▲ 34.8% vs prior (46)
Hit-and-run crashes increased year-over-year, with 62 incidents recorded in December 2025 compared to 46 in December 2024, an increase of 16 crashes. The hit-and-run rate also rose from 14.1% of all crashes in December 2024 to 15.9% in December 2025, indicating an upward trend in hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
4
Pedestrians Injured
2
Cyclists Injured
63
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted between the two periods. In December 2025, the peak day for crashes was Wednesday with 76 incidents, and the peak hour was 3 PM with 41 crashes. This contrasts with December 2024, when Monday recorded the highest number of crashes at 63, and the peak hour was 5 PM with 29 crashes, indicating a shift in peak times.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero in both December 2024 and December 2025, indicating no change in the fatal crash rate. However, total injuries decreased by 31%, from 100 in the prior period to 69 in the current period. Serious injuries (Severity A) decreased from 6 to 3, minor injuries (Severity B) decreased from 47 to 37, and possible injuries (Severity C) decreased from 19 to 14, while crashes with no injury increased from 236 to 310.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, "No improper driving" increased significantly by 50 incidents, from 136 in December 2024 to 186 in December 2025. Conversely, "Followed too closely" saw a substantial decrease of 12 incidents, dropping from 21 in the prior period to 9 in the current period. "Inattention" also decreased by 3 incidents, from 29 to 26, and "Failed to yield right of way" decreased by 7 incidents, from 24 to 17.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 202 in December 2024 to 262 in December 2025, while crashes in rainy conditions decreased from 39 to 27. Notably, crashes during snowy conditions increased significantly from 2 to 19. Regarding road surface, dry road crashes increased from 238 to 284, and snow-covered road crashes increased from 3 to 27, while wet road crashes decreased from 83 to 62.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The age distribution of persons involved in crashes showed shifts, with the 0-15 age group decreasing from 45 to 37 and the 65+ age group decreasing from 96 to 71. Conversely, the 35-44 age group saw an increase from 113 to 146, and the 55-64 age group increased from 54 to 76. Among vehicle makes, Toyota became the most involved with 111 vehicles in December 2025, up from 100, while Honda remained a top make, increasing slightly from 104 to 106.
Top Vehicle Makes (774 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Vehicle unit records
209 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (657 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
The majority of crashes in both periods occurred in the 30 mph speed zone, which saw an increase from 178 crashes in December 2024 to 249 crashes in December 2025. Crashes in the 25 mph zone also slightly increased from 60 to 63. Conversely, crashes in the 65 mph zone decreased from 10 in the prior period to 6 in the current period, indicating a shift of crashes towards lower speed limit zones.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 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: 2025-12-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-12-01 through 2025-12-31 (31 days)
- Geographic scope: NEW BEDFORD, MA
- Total crash records analyzed: 391
- Total persons involved: 888
- Total vehicles involved: 774
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: December 2025." Published June 21, 2026. Reporting period: 2025-12-01 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/december-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: 2025-12-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved