Monthly Traffic Safety Analysis

44 CRASHES IN
SWANSEA, MA
SEPTEMBER 2025

All metrics benchmarked againstSeptember 2024

In September 2025, Swansea experienced 44 crashes, an 8.3% decrease compared to the 48 crashes recorded in September 2024. A notable shift was the increase in hit-and-run crashes, rising from 0 in the prior period to 4 in the current period.

44

-8.3%was 48

Total Crash Events

0

Persons Killed

13

-50.0%was 26

Persons Injured

4

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the number of crashes in Swansea decreased year-over-year, falling from 48 crashes in September 2024 to 44 crashes in September 2025. This represents an 8.3% reduction in total crash incidents for the month.

4

Hit-and-Run Crashes — September 2025

9.1% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

13

Motorists Injured

Prior: 26-50.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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 Wednesday with 9 crashes in September 2024 to Tuesday with 8 crashes in September 2025. The peak crash hour also changed, moving from 3 p.m. with 8 crashes in the prior period to 6 p.m. with 5 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero in both September 2024 and September 2025. Total injuries decreased by 50%, from 26 in the prior period to 13 in the current period. The proportion of crashes resulting in minor injuries fell from 29.2% to 13.6%, while crashes with no injuries increased from 60.4% to 77.3%.

Outcome by Severity (Crash Events)

Minor Injury6minor injury crashes13.6%
-57.1%prior 14
Possible Injury3possible injury crashes6.8%
-40.0%prior 5
No Injury34no injury crashes77.3%
17.2%prior 29

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'Failed to yield right of way,' remained constant with 11 crashes in both periods. Crashes attributed to 'No improper driving' significantly decreased from 11 in September 2024 to 4 in September 2025. Conversely, 'Inattention' related crashes more than doubled, rising from 3 to 7, and 'Followed too closely' incidents increased from 6 to 7 year-over-year.

Officer-Reported Primary Contributing Cause

Failed to yield right of way11 (25%)0.0%prior 11
Inattention7 (15.9%)
Followed too closely7 (15.9%)16.7%prior 6
No improper driving4 (9.1%)-63.6%prior 11
Failure to keep in proper lane or running off road3 (6.8%)-40.0%prior 5
Distracted2 (4.5%)
Glare1 (2.3%)
Fatigued/asleep1 (2.3%)
Other improper action1 (2.3%)
Over-correcting/over-steering1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The number of crashes occurring in 'Clear' weather conditions decreased from 36 in September 2024 to 25 in September 2025, while 'Clear/Cloudy' conditions saw an increase from 1 to 10 crashes. Crashes on 'Wet' road surfaces significantly decreased from 5 in the prior period to just 1 in the current period. Incidents in 'Daylight' conditions decreased from 39 to 36, and crashes in 'Dark - lighted roadway' conditions decreased from 7 to 4.

Weather

Clear25 (56.8%)
-30.6%prior 36
Clear/Cloudy10 (22.7%)
Cloudy4 (9.1%)
Clear/Clear3 (6.8%)
Clear/Other1 (2.3%)
Cloudy/Rain1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Weather condition at time of crash

Lighting

Daylight36 (81.8%)
-7.7%prior 39
Dark - lighted roadway4 (9.1%)
-42.9%prior 7
Dusk2 (4.5%)
Dark - roadway not lighted1 (2.3%)
Dark - unknown roadway lighting1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Lighting condition field

Road Surface

Dry43 (97.7%)
0.0%prior 43
Wet1 (2.3%)
-80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 85 in September 2024 to 81 in September 2025. Ford remained the top make involved, increasing from 12 to 14 vehicles, while Honda involvement decreased from 11 to 8. The 16-20 age group saw a significant increase in representation, from 7 persons in the prior period to 14 in the current period, and the 65+ age group saw a decrease from 21 to 12 persons.

Top Vehicle Makes (81 vehicles)

1
FORD14 (17.3%)
16.7%prior 12
2
TOYOTA9 (11.1%)
0.0%prior 9
3
HYUNDAI8 (9.9%)
4
HONDA8 (9.9%)
-27.3%prior 11
5
CHEVROLET6 (7.4%)
-14.3%prior 7
6
JEEP5 (6.2%)
7
VOLVO3 (3.7%)
8
KIA3 (3.7%)
-50.0%prior 6
9
DODGE2 (2.5%)
10
NISSAN2 (2.5%)
-60.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Vehicle unit records

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

Sex Distribution (89 persons with recorded sex)

Female46 (51.7%)
4.5%prior 44
Male43 (48.3%)
-18.9%prior 53

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones increased from 6 in September 2024 to 9 in September 2025. Conversely, crashes in 25 mph zones decreased from 4 to 1, and 35 mph zones decreased from 10 to 7. Crashes in 50 mph zones remained constant at 8 for both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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: 2025-09-01 through 2025-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-09-01 through 2025-09-30 (30 days)
  • Geographic scope: SWANSEA, MA
  • Total crash records analyzed: 44
  • Total persons involved: 95
  • Total vehicles involved: 81

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). "SWANSEA, MA Crash Intelligence Report: September 2025." Published June 21, 2026. Reporting period: 2025-09-01 to 2025-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/swansea/september-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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Swansea, MA Crash Report — September 2025 | ThatCarHitMe.com