ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEW BEDFORD, MA · JANUARY 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/january-2025-report
Monthly Traffic Safety Analysis
297 CRASHES IN
NEW BEDFORD, MA
JANUARY 2025
In January 2025, NEW BEDFORD, MA recorded 297 total crashes, an increase of 5.32% compared to the 282 crashes in January 2024. While total crashes rose, there were no fatalities in the current period, a notable improvement from the 1 fatality reported in the prior year. Injuries, however, increased by 16.67%, rising from 66 to 77.
297
▲ 5.3%was 282
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
77
▲ 16.7%was 66
Persons Injured
50
▲ 13.6%was 44
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. 21 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 2025-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Total crashes in NEW BEDFORD, MA are trending upwards year-over-year, with a 5.32% increase from 282 crashes in January 2024 to 297 crashes in January 2025. Despite this rise in overall incidents, there was a significant positive shift in safety outcomes, as fatalities decreased from 1 to 0 during the same period. Total injuries, however, saw an increase of 11, rising from 66 to 77.
50
Hit-and-Run Crashes — January 2025
▲ 13.6% vs prior (44)
Hit-and-run crashes increased by 6 incidents, rising from 44 in January 2024 to 50 in January 2025. This represents a 13.64% increase in the count of hit-and-run crashes year-over-year. The hit-and-run rate also saw an increase, climbing from 15.6% of total crashes in the prior period to 16.8% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
4
Pedestrians Injured
1
Cyclists Injured
70
Motorists Injured
2
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes shifted significantly year-over-year. Friday became the peak day for crashes in January 2025 with 63 incidents, a substantial increase from 32 crashes on Fridays in January 2024, when Wednesday was the peak day with 49 crashes. The peak hour also changed, moving from 2 p.m. with 34 crashes in the prior period to 3 p.m. with 32 crashes in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities saw a positive change, decreasing from 1 in January 2024 to 0 in January 2025. Total injuries increased by 11, from 66 to 77 year-over-year. Crashes resulting in serious injury (A) increased from 2 (0.7% of total crashes) to 3 (1.0%), and minor injury (B) crashes rose from 33 (11.7%) to 44 (14.8%). Conversely, crashes with possible injury (C) decreased from 16 (5.7%) to 12 (4.0%) year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor, 'No improper driving,' increased by 42 crashes, from 87 in January 2024 to 129 in January 2025, also increasing its share from 30.9% to 43.4% of all factors. 'Inattention' decreased by 8 crashes, from 30 to 22, while 'Other improper action' increased by 4 crashes, from 15 to 19. Notably, crashes attributed to 'Distracted' driving increased by 4, from 1 to 5, and 'Exceeded authorized speed limit' crashes increased by 3, from 1 to 4.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased from 145 in January 2024 to 209 in January 2025, while crashes in 'Rain' and 'Snow' conditions decreased from 22 to 17 and 15 to 6, respectively. Crashes on 'Dry' road surfaces increased from 189 to 235, whereas those on 'Wet' surfaces decreased from 65 to 35. The number of crashes occurring in 'Daylight' increased from 156 to 174, while those in 'Dark - lighted roadway' decreased from 102 to 89.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 30, from 551 in January 2024 to 581 in January 2025. Toyota became the most frequently involved vehicle make, with 98 instances, surpassing Honda which decreased from 76 to 65. The 35-44 age group saw the largest increase in persons involved, rising from 79 to 96, while the 26-34 age group experienced the largest decrease, falling from 114 to 88.
Top Vehicle Makes (581 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Vehicle unit records
153 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (511 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed limit zone saw a minor increase from 153 to 154, while crashes in the 25 mph zone increased from 55 to 66. There were no fatalities in any speed zone in January 2025, compared to 1 fatality in the 30 mph zone in January 2024. Crashes in the 20 mph zone decreased from 23 to 15, and those in the 55 mph zone decreased from 11 to 7.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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 2025-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-01-31 (31 days)
- Geographic scope: NEW BEDFORD, MA
- Total crash records analyzed: 297
- Total persons involved: 681
- Total vehicles involved: 581
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: January 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/new-bedford/january-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: 2025-01-01 – 2025-01-31
Generated: June 21, 2026 · All rights reserved