Monthly Traffic Safety Analysis

36 CRASHES IN
WESTPORT, MA
MAY 2025

All metrics benchmarked againstMay 2024

Total crashes in Westport increased from 34 in May 2024 to 36 in May 2025, representing a 5.9% rise. The most significant year-over-year shift was a 150% increase in total injuries, rising from 4 to 10. This indicates a notable increase in crash severity despite a small increase in overall crash count.

36

5.9%was 34

Total Crash Events

0

Persons Killed

10

150.0%was 4

Persons Injured

2

-33.3%was 3

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in Westport show a slight increase, with total crashes rising by 5.9% from 34 in May 2024 to 36 in May 2025. This represents an increase of 2 crashes year-over-year. The number of injured persons, however, saw a substantial increase from 4 to 10, a 150% rise.

2

Hit-and-Run Crashes — May 2025

-33.3% vs prior (3)

The number of hit-and-run crashes decreased from 3 in May 2024 to 2 in May 2025. Consequently, the hit-and-run crash rate decreased from 8.8% to 5.6% year-over-year. This indicates a downward trend in the proportion of hit-and-run incidents.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

10

Motorists Injured

Prior: 4150.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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 year-over-year. In May 2025, the peak day for crashes was Thursday with 11 incidents, a change from Tuesday with 8 incidents in May 2024. The peak hour also shifted from 8 AM with 5 crashes in May 2024 to 4 PM with 5 crashes in May 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While no fatal crashes occurred in either period, there was a substantial increase in injuries. Total injuries rose by 150%, from 4 in May 2024 to 10 in May 2025. The proportion of minor injuries increased from 5.9% to 13.9%, and possible injuries increased from 5.9% to 8.3% of all crashes.

Outcome by Severity (Crash Events)

Minor Injury5minor injury crashes13.9%
150.0%prior 2
Possible Injury3possible injury crashes8.3%
50.0%prior 2
No Injury28no injury crashes77.8%
-3.4%prior 29

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "No improper driving" increased by 4 incidents, from 10 in May 2024 to 14 in May 2025. "Inattention" decreased by 4 incidents, from 7 to 3. "Failed to yield right of way" increased from 1 incident in May 2024 to 5 incidents in May 2025, while "Distracted" contributing factors, which accounted for 4 incidents in May 2024, were not among the top factors in May 2025.

Officer-Reported Primary Contributing Cause

No improper driving14 (38.9%)40.0%prior 10
Failed to yield right of way5 (13.9%)
Inattention3 (8.3%)-57.1%prior 7
Other improper action2 (5.6%)
Followed too closely2 (5.6%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (2.8%)
Visibility obstructed1 (2.8%)
Made an improper turn1 (2.8%)
Failure to keep in proper lane or running off road1 (2.8%)
Fatigued/asleep1 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions remained relatively stable, with 28 incidents in May 2025 compared to 26 in May 2024. The number of crashes on wet road surfaces increased from 4 in May 2024 to 6 in May 2025. The number of crashes occurring in dark or low-light conditions remained stable at 7 incidents in both periods.

Weather

Clear21 (58.3%)
-4.5%prior 22
Clear/Clear6 (16.7%)
Cloudy4 (11.1%)
Cloudy/Rain1 (2.8%)
Rain1 (2.8%)
Rain/Cloudy1 (2.8%)
Clear/Unknown1 (2.8%)
Cloudy/Cloudy1 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash

Lighting

Daylight29 (80.6%)
7.4%prior 27
Dark - roadway not lighted3 (8.3%)
-50.0%prior 6
Dawn2 (5.6%)
Dark - lighted roadway1 (2.8%)
Dusk1 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field

Road Surface

Dry30 (83.3%)
0.0%prior 30
Wet6 (16.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (65 vehicles)

1
TOYOTA11 (16.9%)
120.0%prior 5
2
NISSAN7 (10.8%)
3
HONDA6 (9.2%)
-33.3%prior 9
4
FORD6 (9.2%)
5
CHEVROLET5 (7.7%)
6
HYUNDAI3 (4.6%)
7
VOLKSWAGEN2 (3.1%)
8
JEEP2 (3.1%)
9
MAZDA2 (3.1%)
10
GMC2 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records

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

Sex Distribution (88 persons with recorded sex)

Male47 (53.4%)
67.9%prior 28
Female41 (46.6%)
70.8%prior 24

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones decreased from 7 in May 2024 to 4 in May 2025, while crashes in 35 mph zones increased from 3 to 7. Crashes in 55 mph zones decreased from 6 to 2, but crashes in 65 mph zones increased from 7 to 9. This indicates a shift in crash distribution across certain speed limit categories.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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: 2025-05-01 through 2025-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-05-01 through 2025-05-31 (31 days)
  • Geographic scope: WESTPORT, MA
  • Total crash records analyzed: 36
  • Total persons involved: 93
  • Total vehicles involved: 65

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). "WESTPORT, MA Crash Intelligence Report: May 2025." Published June 21, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/westport/may-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

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Westport, MA Crash Report — May 2025 | ThatCarHitMe.com