Monthly Traffic Safety Analysis

101 CRASHES IN
BARNSTABLE, MA
MAY 2025

All metrics benchmarked againstMay 2024

In May 2025, BARNSTABLE experienced 101 crashes, a decrease of 14.4% compared to 118 crashes in May 2024. The most significant year-over-year shift was the presence of 1 fatality in May 2025, compared to zero fatalities in the prior year.

101

-14.4%was 118

Total Crash Events

1

Persons Killed

25

-19.4%was 31

Persons Injured

5

-44.4%was 9

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

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, BARNSTABLE saw a decrease in total crashes, falling by 14.4% from 118 in May 2024 to 101 in May 2025. Total injuries also decreased by 19.35%, from 31 to 25. However, there was a concerning increase in fatalities, with 1 fatality reported in May 2025 compared to none in May 2024.

5

Hit-and-Run Crashes — May 2025

-44.4% vs prior (9)

Hit-and-run crashes decreased from 9 incidents in May 2024 to 5 incidents in May 2025. Correspondingly, the hit-and-run rate fell from 7.6% of total crashes in May 2024 to 5% in May 2025.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

0

Other Killed

Prior: 00.0%

2

Cyclists Injured

Prior: 0%

22

Motorists Injured

Prior: 31-29.0%

1

Other Injured

Prior: 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 peak day for crashes shifted from Thursday in May 2024 (24 crashes) to Friday in May 2025 (20 crashes), though both saw a reduction in peak counts. The peak crash hour remained 4 PM, with 12 crashes in May 2025 compared to 11 in May 2024. Notably, crashes on Sunday increased from 3 in May 2024 to 10 in May 2025, while Monday crashes decreased significantly from 19 to 10.

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

The severity distribution saw a notable change with the introduction of 1 fatal crash in May 2025, where there were none in May 2024. Serious injury crashes remained consistent at 4 incidents in both periods, but their share of total crashes increased from 3.4% to 4%. Minor injury crashes increased from 11 to 13, while possible injury crashes decreased from 8 to 6 year-over-year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1%
Serious Injury4serious injury crashes4%
0.0%prior 4
Minor Injury13minor injury crashes12.9%
18.2%prior 11
Possible Injury6possible injury crashes5.9%
-25.0%prior 8
No Injury75no injury crashes74.3%
-20.2%prior 94

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

The top contributing factors show shifts in prevalence. 'Inattention' crashes increased by 5, from 18 in May 2024 to 23 in May 2025, making it a leading factor. Conversely, crashes attributed to 'No improper driving' decreased by 7, from 30 to 23, and 'Failed to yield right of way' crashes decreased by 6, from 18 to 12. 'Followed too closely' crashes also saw a significant reduction, dropping from 8 to 4, a 50% decrease in count.

Officer-Reported Primary Contributing Cause

Inattention23 (22.8%)27.8%prior 18
No improper driving23 (22.8%)-23.3%prior 30
Failed to yield right of way12 (11.9%)-33.3%prior 18
Distracted5 (5%)
Followed too closely4 (4%)-50.0%prior 8
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (4%)-42.9%prior 7
Disregarded traffic signs, signals, road markings3 (3%)-40.0%prior 5
Visibility obstructed3 (3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (2%)
Failure to keep in proper lane or running off road2 (2%)

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 decreased from 77 in May 2024 to 74 in May 2025, and crashes in 'Cloudy' conditions also fell from 18 to 10. Similarly, crashes on 'Dry' road surfaces decreased from 99 to 90, and 'Wet' road surface crashes decreased from 19 to 11. The proportion of crashes occurring during 'Daylight' decreased from 102 to 85, while crashes in 'Dark - lighted roadway' conditions slightly increased from 7 to 8.

Weather

Clear74 (73.3%)
-3.9%prior 77
Cloudy10 (9.9%)
-44.4%prior 18
Rain4 (4.0%)
-42.9%prior 7
Clear/Clear3 (3.0%)
Clear/Cloudy3 (3.0%)
Clear/Unknown2 (2.0%)
-66.7%prior 6
Rain/Cloudy2 (2.0%)
Rain/Rain1 (1.0%)
Cloudy/Clear1 (1.0%)
Cloudy/Rain1 (1.0%)
-80.0%prior 5

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

Lighting

Daylight85 (84.2%)
-16.7%prior 102
Dark - lighted roadway8 (7.9%)
14.3%prior 7
Dark - roadway not lighted5 (5.0%)
-16.7%prior 6
Dawn2 (2.0%)
Dark - unknown roadway lighting1 (1.0%)

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

Road Surface

Dry90 (89.1%)
-9.1%prior 99
Wet11 (10.9%)
-42.1%prior 19

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

Vehicles & Demographics

The age distribution of persons involved in crashes saw shifts, with increases in the 0-15 age group (from 11 to 14) and 16-20 age group (from 20 to 25). Conversely, most other age groups, particularly 26-34 and 35-44, experienced decreases in involvement. Toyota became the most frequently involved vehicle make in May 2025 with 32 vehicles, surpassing Ford and Honda which saw decreases from 31 to 20 and 30 to 18 respectively.

Top Vehicle Makes (182 vehicles)

1
TOYOTA32 (17.6%)
23.1%prior 26
2
FORD20 (11%)
-35.5%prior 31
3
HONDA18 (9.9%)
-40.0%prior 30
4
CHEVROLET17 (9.3%)
-19.0%prior 21
5
HYUNDAI9 (4.9%)
0.0%prior 9
6
JEEP8 (4.4%)
-33.3%prior 12
7
NISSAN6 (3.3%)
-50.0%prior 12
8
AUDI5 (2.7%)
9
SUBARU5 (2.7%)
-54.5%prior 11
10
VOLKSWAGEN5 (2.7%)

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

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

Sex Distribution (210 persons with recorded sex)

Male125 (59.5%)
-12.6%prior 143
Female85 (40.5%)
-18.3%prior 104

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

The distribution of crashes across speed zones saw minor changes, with crashes in the 30 mph zone decreasing slightly from 40 in May 2024 to 38 in May 2025. Notably, the single fatal crash in May 2025 occurred in a 30 mph speed zone, whereas no fatal crashes were reported in any speed zone in May 2024. Crashes in the 25 mph zone were halved, from 12 to 6, and crashes in the 55 mph zone also decreased from 7 to 3.

Fatal crashes by zone: 30 mph: 1 of 38 (2.632%)

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: BARNSTABLE, MA
  • Total crash records analyzed: 101
  • Total persons involved: 230
  • Total vehicles involved: 182

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). "BARNSTABLE, 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/barnstable/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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Barnstable, MA Crash Report — May 2025 | ThatCarHitMe.com