Monthly Traffic Safety Analysis

8 CRASHES IN
WELLFLEET, MA
MAY 2023

All metrics benchmarked againstMay 2022

Total crashes in WELLFLEET, MA decreased by 20% from 10 crashes in May 2022 to 8 crashes in May 2023. This reduction in overall crash incidents represents the most notable year-over-year shift for the period.

8

-20.0%was 10

Total Crash Events

0

Persons Killed

0

Persons Injured

1

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. 8 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in WELLFLEET, MA show a downward trend, decreasing by 20% from 10 crashes in May 2022 to 8 crashes in May 2023. This indicates a reduction in traffic incidents for the specified month compared to the prior year.

1

Hit-and-Run Crashes — May 2023

12.5% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

When Crashes Happen

The temporal patterns of crashes shifted significantly year-over-year. The peak day for crashes moved from Tuesday with 4 incidents in May 2022 to Friday with 3 incidents in May 2023. Similarly, the peak hour for crashes shifted from 12p with 4 incidents in May 2022 to 8p with 3 incidents in May 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash time field aggregated by hour (0-23)

Top Contributing Factors

The top contributing factor, 'No improper driving', remained constant with 4 crashes in both May 2022 and May 2023. Crashes attributed to 'Inattention' decreased from 2 in May 2022 to 1 in May 2023, representing a 50% reduction in count. Factors like 'Followed too closely' and 'Other improper action' each accounted for 1 crash in May 2023, whereas they were not among the top reported factors in May 2022.

Officer-Reported Primary Contributing Cause

No improper driving4 (50%)
Followed too closely1 (12.5%)
Inattention1 (12.5%)
Other improper action1 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

In May 2023, 4 crashes occurred during Daylight conditions, while 4 crashes occurred in dark conditions (2 in 'Dark - lighted roadway' and 2 in 'Dark - roadway not lighted'). In May 2022, 9 crashes occurred during Daylight and 1 in 'Dark - lighted roadway'. The proportion of crashes occurring in dark conditions increased from 10% in May 2022 to 50% in May 2023.

Weather

Clear7 (87.5%)
Rain/Other1 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash

Lighting

Daylight4 (50.0%)
-55.6%prior 9
Dark - lighted roadway2 (25.0%)
Dark - roadway not lighted2 (25.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field

Road Surface

Dry7 (87.5%)
Wet1 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (14 vehicles)

1
TOYOTA5 (35.7%)
2
CHRYSLER1 (7.1%)
3
DODGE1 (7.1%)
4
FORD1 (7.1%)
5
HONDA1 (7.1%)
6
HYUNDAI1 (7.1%)
7
JEEP1 (7.1%)
8
MITS1 (7.1%)
9
ACURA1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records

1 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (17 persons with recorded sex)

Male11 (64.7%)
10.0%prior 10
Female6 (35.3%)
-40.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone decreased from 2 in May 2022 to 1 in May 2023, while crashes in the 45 mph speed zone decreased from 5 to 3. May 2023 data also included crashes in 5 mph (1 crash) and 25 mph (3 crashes) zones, which were not represented in May 2022 crash data. Both periods reported 0 fatalities across all speed zones.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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: 2023-05-01 through 2023-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-05-01 through 2023-05-31 (31 days)
  • Geographic scope: WELLFLEET, MA
  • Total crash records analyzed: 8
  • Total persons involved: 18
  • Total vehicles involved: 14

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: May 2023." Published June 21, 2026. Reporting period: 2023-05-01 to 2023-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wellfleet/may-2023-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

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Wellfleet, MA Crash Report — May 2023 | ThatCarHitMe.com