ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEW BEDFORD, MA · AUGUST 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/august-2025-report
Monthly Traffic Safety Analysis
336 CRASHES IN
NEW BEDFORD, MA
AUGUST 2025
In August 2025, New Bedford experienced 336 total crashes, an increase of 17.07% compared to the 287 crashes reported in August 2024. While total fatalities remained stable at 1, total injuries decreased by 17.43% from 109 to 90. The most notable year-over-year shift was a 91.67% increase in hit-and-run crashes, rising from 36 to 69 incidents.
336
▲ 17.1%was 287
Total Crash Events
1
Persons Killed
90
▼ -17.4%was 109
Persons Injured
69
▲ 91.7%was 36
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 33 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in New Bedford increased year-over-year, with total crashes rising by 17.07% from 287 to 336. Total fatalities remained stable at 1 in both periods. Conversely, total injuries decreased by 17.43%, from 109 in August 2024 to 90 in August 2025.
69
Hit-and-Run Crashes — August 2025
▲ 91.7% vs prior (36)
Hit-and-run crashes increased significantly by 33 incidents, rising from 36 in August 2024 to 69 in August 2025. This resulted in the hit-and-run rate increasing from 12.5% to 20.5% of total crashes, an 8 percentage point rise. The data indicates an upward trend in hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
2
Pedestrians Injured
6
Cyclists Injured
78
Motorists Injured
4
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Saturday in both periods, though the count decreased from 62 in August 2024 to 58 in August 2025. The peak hour shifted from 4 p.m. in the prior period, which had 28 crashes, to 3 p.m. in the current period, which recorded 32 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at 1 in both August 2024 and August 2025, with the fatal crash rate decreasing slightly from 0.35% to 0.3%. Serious injury crashes also remained at 10 incidents, but their share of total crashes decreased from 3.5% to 3%. Minor injury crashes decreased from 47 to 39, and possible injury crashes decreased from 19 to 13.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, 'No improper driving', increased by 30 crashes, from 112 to 142. 'Inattention' also increased by 8 crashes, from 19 to 27. 'Failed to yield right of way' decreased by 9 crashes, from 21 to 12, while 'Disregarded traffic signs, signals, road markings' saw a substantial increase of 9 crashes, rising from 3 to 12.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 220 to 264, while rain-related crashes decreased from 7 to 4. Crashes during daylight hours increased from 203 to 233, and incidents in 'Dark - lighted roadway' conditions decreased slightly from 68 to 66. Crashes on dry road surfaces increased from 265 to 310, whereas crashes on wet road surfaces decreased from 18 to 12.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes increased from 708 to 780 year-over-year. The 35-44 age group saw an increase of 14 persons involved, from 91 to 105, while the 45-54 age group experienced a decrease of 23 persons, from 81 to 58. Toyota became the top vehicle make with 90 vehicles involved, up from 83, while Honda remained at 90 vehicles involved.
Top Vehicle Makes (673 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Vehicle unit records
206 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (544 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone significantly increased from 162 to 223 incidents. Conversely, crashes in the 25 mph speed zone decreased from 61 to 49 incidents. The 35 mph speed zone recorded 1 fatal crash in the current period, compared to none in the prior period, with total crashes in this zone increasing from 9 to 12.
Fatal crashes by zone: 35 mph: 1 of 12 (8.333%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · 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: 2025-08-01 through 2025-08-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-08-01 through 2025-08-31 (31 days)
- Geographic scope: NEW BEDFORD, MA
- Total crash records analyzed: 336
- Total persons involved: 780
- Total vehicles involved: 673
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: August 2025." Published June 21, 2026. Reporting period: 2025-08-01 to 2025-08-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/new-bedford/august-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: 2025-08-01 – 2025-08-31
Generated: June 21, 2026 · All rights reserved