Monthly Traffic Safety Analysis

66 CRASHES IN
SEEKONK, MA
JUNE 2025

All metrics benchmarked againstJune 2024

SEEKONK experienced a notable increase in crash incidents, with total crashes rising from 48 in June 2024 to 66 in June 2025, representing a 37.5% increase. The most significant year-over-year shift was a 90% increase in total injuries, climbing from 10 to 19. Additionally, hit-and-run crashes doubled from 3 to 6 incidents.

66

37.5%was 48

Total Crash Events

0

Persons Killed

19

90.0%was 10

Persons Injured

6

100.0%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 · 2025-06-01 to 2025-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in SEEKONK showed an upward trend year-over-year, with total crashes increasing by 37.5% from 48 in June 2024 to 66 in June 2025. Total injuries also saw a substantial rise of 90%, from 10 to 19. Fatalities remained at zero in both periods.

6

Hit-and-Run Crashes — June 2025

100.0% vs prior (3)

Hit-and-run crashes doubled year-over-year, increasing from 3 incidents in June 2024 to 6 in June 2025. Consequently, the hit-and-run rate increased from 6.3% of total crashes in the prior period to 9.1% in the current period, indicating an upward trend.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 3-66.7%

18

Motorists Injured

Prior: 7157.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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; the peak day for crashes moved from Sunday in June 2024 (14 crashes) to Friday in June 2025 (12 crashes). The peak hour for crashes remained consistent at 1 p.m. in June 2024 and 3 p.m. in June 2025, both recording 8 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Total injuries increased from 10 in June 2024 to 19 in June 2025, a 90% rise. While June 2024 reported 1 serious injury (2.1% of crashes), June 2025 had no serious injuries. Minor injuries increased from 5 to 7, and possible injuries increased from 4 to 7 year-over-year.

Outcome by Severity (Crash Events)

Minor Injury7minor injury crashes10.6%
40.0%prior 5
Possible Injury7possible injury crashes10.6%
75.0%prior 4
No Injury52no injury crashes78.8%
40.5%prior 37

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'No improper driving' saw a significant increase in count, rising from 9 in June 2024 to 21 in June 2025, a 133.3% change. Conversely, 'Inattention' decreased by 50% in count, from 16 to 8 crashes. 'Failed to yield right of way' also increased from 6 to 10 crashes, a 66.7% change.

Officer-Reported Primary Contributing Cause

No improper driving21 (31.8%)133.3%prior 9
Failed to yield right of way10 (15.2%)66.7%prior 6
Inattention8 (12.1%)-50.0%prior 16
Followed too closely6 (9.1%)-14.3%prior 7
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner5 (7.6%)
Other improper action3 (4.5%)
Exceeded authorized speed limit2 (3%)
Failure to keep in proper lane or running off road2 (3%)
Made an improper turn1 (1.5%)
Distracted1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring under 'Clear' weather conditions increased from 40 in June 2024 to 52 in June 2025. Similarly, crashes during 'Daylight' conditions rose from 40 to 53 incidents year-over-year. Crashes on 'Dry' road surfaces also increased, from 42 to 61, while those on 'Wet' surfaces slightly decreased from 6 to 5.

Weather

Clear52 (78.8%)
30.0%prior 40
Clear/Clear7 (10.6%)
Cloudy3 (4.5%)
Rain/Cloudy3 (4.5%)
Cloudy/Rain1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Weather condition at time of crash

Lighting

Daylight53 (80.3%)
32.5%prior 40
Dark - roadway not lighted5 (7.6%)
Dark - lighted roadway4 (6.1%)
-42.9%prior 7
Dusk3 (4.5%)
Dawn1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Lighting condition field

Road Surface

Dry61 (92.4%)
45.2%prior 42
Wet5 (7.6%)
-16.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 31.9%, from 91 in June 2024 to 120 in June 2025. Toyota remained the top make involved, increasing from 13 to 21 vehicles, while Hyundai decreased from 10 to 5. The 21-25 age group saw the largest increase in persons involved, rising from 15 to 25.

Top Vehicle Makes (120 vehicles)

1
TOYOTA21 (17.5%)
61.5%prior 13
2
FORD12 (10%)
0.0%prior 12
3
HONDA11 (9.2%)
0.0%prior 11
4
CHEVROLET11 (9.2%)
57.1%prior 7
5
NISSAN7 (5.8%)
6
GMC6 (5%)
7
KIA5 (4.2%)
8
HYUNDAI5 (4.2%)
-50.0%prior 10
9
JEEP5 (4.2%)
10
SUBARU4 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Vehicle unit records

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

Sex Distribution (132 persons with recorded sex)

Male80 (60.6%)
3.9%prior 77
Female52 (39.4%)
44.4%prior 36

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 40 mph speed zones increased from 18 in June 2024 to 26 in June 2025. There was also a notable increase in crashes within 65 mph zones, rising from 1 to 8 incidents. Crashes in 5 mph zones decreased from 6 to 4 year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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: 2025-06-01 through 2025-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-06-01 through 2025-06-30 (30 days)
  • Geographic scope: SEEKONK, MA
  • Total crash records analyzed: 66
  • Total persons involved: 143
  • Total vehicles involved: 120

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). "SEEKONK, MA Crash Intelligence Report: June 2025." Published June 21, 2026. Reporting period: 2025-06-01 to 2025-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/seekonk/june-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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Seekonk, MA Crash Report — June 2025 | ThatCarHitMe.com