ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WELLFLEET, MA · 2023
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/2023-annual-report
Yearly Traffic Safety Analysis
97 CRASHES IN
WELLFLEET, MA
2023
In Wellfleet, total vehicle crashes remained nearly stable, with 97 incidents in 2023 compared to 98 in 2022, a decrease of approximately 1%. While the overall crash volume was consistent, the most notable year-over-year shift was a significant increase in the number of injuries, which rose from 15 to 39. Concurrently, the number of fatalities dropped from one in the prior year to zero in the current year.
97
▼ -1.0%was 98
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
39
▲ 160.0%was 15
Persons Injured
6
▲ 20.0%was 5
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. 6 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend in crash volume shows stability, with a marginal decrease of just one crash from 98 in 2022 to 97 in 2023. However, the severity of outcomes worsened, as total injuries increased by 160% from 15 to 39. This was offset by a positive trend in fatalities, which decreased from one person killed in 2022 to zero in 2023.
6
Hit-and-Run Crashes — 2023
▲ 20.0% vs prior (5)
Hit-and-run incidents saw a slight increase in both count and rate. The number of hit-and-run crashes rose from 5 in 2022 to 6 in 2023. As a percentage of all crashes, the hit-and-run rate also trended up, increasing from 5.1% in the prior year to 6.2% in the current year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
37
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. The peak day for crashes moved from Tuesday (22 crashes) in 2022 to Friday (19 crashes) in 2023. Similarly, the peak hour for incidents changed from 1 p.m. in the prior year (15 crashes) to 11 a.m. in the current year (12 crashes). Both years exhibited a seasonal peak in the summer months, with July having the highest number of crashes in both 2022 (25) and 2023 (19).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity outcomes changed significantly year-over-year. Fatal crashes decreased from one in 2022 to zero in 2023. However, the number of crashes resulting in minor injuries more than quadrupled, rising from 4 incidents (4.1% of total) in 2022 to 17 (17.5% of total) in 2023. The count of serious injury crashes also doubled from 2 to 4. Consequently, the proportion of non-injury crashes fell from 87.8% of all incidents in 2022 to 68% in 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
In 2023, 'No improper driving' was the most cited factor with 34 crashes, an increase from 26 in 2022. 'Inattention' was the second-leading factor in 2023 with 19 crashes, a decrease from 23 crashes in the prior year when it was the top factor. The count of crashes attributed to an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' increased from 7 to 10. Incidents involving 'Followed too closely' more than doubled, rising from 3 crashes in 2022 to 7 in 2023.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes under adverse conditions saw an increase in 2023 compared to 2022. While 'Dry' road surfaces and 'Clear' weather still accounted for the majority of incidents in both years, crashes on 'Wet' roads more than doubled from 6 to 14. Similarly, crashes in 'Rain' increased from 1 to 5. Collisions in 'Daylight' remained most common but decreased from 82 to 67, while crashes on dark but lighted roadways increased from 5 to 14.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
Vehicle and person demographics showed some shifts between periods. Toyota remained the most frequently involved vehicle make in both years, with its count increasing from 29 in 2022 to 37 in 2023. Ford's involvement increased from 15 to 22 vehicles, moving it from fourth to second place. The 55-64 age group was the most represented among persons involved in crashes in both years, with its count rising from 41 to 56. The 65+ age group also saw a notable increase in involvement, from 38 persons in 2022 to 51 in 2023.
Top Vehicle Makes (166 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
16 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (209 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones changed year-over-year. The 45 mph zone continued to see the highest number of crashes, increasing from 49 in 2022 to 55 in 2023. Crashes in 25 mph zones more than doubled from 9 to 22, while crashes in 30 mph zones were cut by more than half, falling from 19 to 9. The single fatal crash in 2022 occurred in a 45 mph zone; no fatal crashes were recorded in any speed zone in 2023.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: WELLFLEET, MA
- Total crash records analyzed: 97
- Total persons involved: 225
- Total vehicles involved: 166
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wellfleet/2023-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved