ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WELLFLEET, 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/wellfleet/2025-annual-report
Yearly Traffic Safety Analysis
112 CRASHES IN
WELLFLEET, MA
2025
In 2025, Wellfleet recorded 112 total crashes, an increase of 7.7% from the 104 crashes reported in 2024. While the total number of fatalities remained stable at one per year, the most notable year-over-year shift was the emergence of pedestrian-involved collisions. After recording zero pedestrian crashes in 2024, there were four such incidents in 2025, including the year's single fatal crash.
112
▲ 7.7%was 104
Total Crash Events
1
Persons Killed
37
▲ 2.8%was 36
Persons Injured
6
▲ 100.0%was 3
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. 4 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
Overall traffic crash trends in Wellfleet are rising. Total crashes increased by 7.7% from 104 in 2024 to 112 in 2025. The number of injuries saw a slight corresponding increase from 36 to 37, while the number of fatalities remained unchanged at one death in each period.
6
Hit-and-Run Crashes — 2025
▲ 100.0% vs prior (3)
Hit-and-run crashes trended upward in 2025. The total count of hit-and-run incidents doubled from 3 in 2024 to 6 in 2025. This increase is also reflected in the hit-and-run rate as a percentage of total crashes, which rose from 2.9% to 5.4% year-over-year.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Motorists Killed
0
Other Killed
1
Pedestrians Injured
35
Motorists Injured
1
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
The temporal patterns of crashes shifted in 2025, with the peak day for collisions moving from Thursday (16 crashes) to Friday (21 crashes). The daily peak hour for crashes also shifted slightly later, from 3 PM in 2024 to 4 PM in 2025. The concentration of crashes during the summer months of July and August intensified, increasing from 40 incidents in 2024 to 50 in 2025, representing 45% of the year's total.
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 overall severity of crashes showed a mixed profile. The fatal crash rate per 100 crashes decreased from 0.96 to 0.89, although the absolute count of fatal crashes was stable at one. The proportion of crashes resulting in any level of injury (Fatal, Serious, Minor, or Possible) declined from 28.8% in 2024 to 22.3% in 2025. Consequently, the share of crashes with no reported injuries increased from 71.2% to 74.1% year-over-year.
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 ranking of top contributing factors shifted between 2024 and 2025. Crashes attributed to 'Inattention' increased in count by 63.6% from 11 to 18, moving from the third to the second most common factor. Conversely, 'Failed to yield right of way' incidents decreased in count by 53.3% from 15 to 7, falling from the second-ranked to the third-ranked factor. 'No improper driving' remained the most frequently cited factor in both years, with its count increasing from 34 to 46.
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
In 2025, a higher proportion of crashes occurred during daylight hours, which accounted for 82.1% of incidents compared to 76.9% in the prior year. However, the share of crashes happening in adverse weather conditions like rain or cloudy skies also grew, rising from 15.4% in 2024 to 23.2% in 2025. The proportion of crashes on dry road surfaces remained relatively stable, at 83.9% in 2025 versus 85.6% in 2024.
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
Toyota remained the vehicle make most frequently involved in crashes, though its count decreased from 43 in 2024 to 35 in 2025. Among persons involved in crashes, the 16-20 age group saw a notable increase in representation, growing from 12 individuals in 2024 to 20 in 2025 and raising their share of total persons from 5.2% to 8.0%. The 65+ age group continued to be the largest demographic involved in crashes, with their count rising from 69 to 74, while their share remained stable near 30%.
Top Vehicle Makes (200 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
24 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (225 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
A significant redistribution of crashes occurred across speed zones. Crashes in 35 mph zones saw a dramatic increase from 1 incident in 2024 to 13 in 2025. In contrast, crashes in 45 mph zones decreased from 49 to 38. The single fatal crash in both 2024 and 2025 occurred in a 35 mph zone.
Fatal crashes by zone: 35 mph: 1 of 13 (7.692%)
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: WELLFLEET, MA
- Total crash records analyzed: 112
- Total persons involved: 250
- Total vehicles involved: 200
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). "WELLFLEET, 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/wellfleet/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