Monthly Traffic Safety Analysis

12 CRASHES IN
SWAMPSCOTT, MA
MAY 2025

All metrics benchmarked againstMay 2024

The total number of crashes in Swampscott increased from 10 in May 2024 to 12 in May 2025, representing a 20% rise. Despite this increase in total crashes, the number of total injuries decreased significantly by 71.4%, from 7 injuries in May 2024 to 2 injuries in May 2025. Notably, DUI-related crashes, which accounted for 20% of crashes in May 2024, were absent in May 2025.

12

20.0%was 10

Total Crash Events

0

Persons Killed

2

-71.4%was 7

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.

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, Swampscott experienced an increase in total crashes by 20%, rising from 10 in May 2024 to 12 in May 2025. However, total injuries saw a substantial decrease of 71.4%, falling from 7 in May 2024 to 2 in May 2025. Fatalities remained at zero in both periods.

1

Hit-and-Run Crashes — May 2025

8.3% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 0%

1

Motorists Injured

Prior: 5-80.0%

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 showed shifts between the two periods. While Friday had the highest crash count in May 2024 with 3 crashes, May 2025 saw Saturday and Friday tied for the highest crash count, each with 3 incidents. The peak hour for crashes shifted from 3 p.m. in May 2024 (3 crashes) to 5 p.m. in May 2025 (2 crashes), indicating a later concentration of incidents.

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 overall severity profile of crashes improved year-over-year, with total injuries decreasing from 7 in May 2024 to 2 in May 2025. Specifically, minor injuries, which accounted for 40% of crashes in May 2024, were absent in May 2025. While serious injury crashes remained at one incident in both periods, possible injury crashes emerged in May 2025 with one incident, compared to none in May 2024.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes8.3%
0.0%prior 1
Possible Injury1possible injury crashes8.3%
No Injury10no injury crashes83.3%
100.0%prior 5

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 distribution of contributing factors shifted between May 2024 and May 2025. Crashes attributed to 'No improper driving' decreased from 5 to 4 incidents, while 'Inattention' as a factor increased significantly from 1 to 3 incidents. Notably, 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased from 2 incidents to zero, and new factors like 'Fatigued/asleep,' 'Failed to yield right of way,' and 'Made an improper turn' each emerged with one incident in May 2025.

Officer-Reported Primary Contributing Cause

No improper driving4 (33.3%)-20.0%prior 5
Inattention3 (25%)
Fatigued/asleep1 (8.3%)
Failed to yield right of way1 (8.3%)
Made an improper turn1 (8.3%)
Failure to keep in proper lane or running off road1 (8.3%)

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

The weather conditions during crashes became more varied in May 2025, with incidents in 'Clear' conditions decreasing from 9 to 6, while 'Cloudy' conditions increased from zero to 4 incidents. 'Daylight' remained the dominant lighting condition, increasing from 8 to 10 incidents, and crashes occurring in 'Dark - lighted roadway' conditions remained stable at 2 incidents in both periods.

Weather

Clear6 (50.0%)
-33.3%prior 9
Cloudy4 (33.3%)
Clear/Cloudy1 (8.3%)
Cloudy/Cloudy1 (8.3%)

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

Lighting

Daylight10 (83.3%)
25.0%prior 8
Dark - lighted roadway2 (16.7%)

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

Road Surface

Dry11 (91.7%)
Wet1 (8.3%)

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 (19 vehicles)

1
TOYOTA5 (26.3%)
2
FORD2 (10.5%)
3
HYUNDAI2 (10.5%)
4
AUDI2 (10.5%)
5
MERCEDES-BENZ2 (10.5%)
6
VOLVO1 (5.3%)
7
NISSAN1 (5.3%)
8
PTRB1 (5.3%)
9
SUBARU1 (5.3%)
10
LEXUS1 (5.3%)

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

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

Sex Distribution (23 persons with recorded sex)

Male15 (65.2%)
7.1%prior 14
Female8 (34.8%)
-11.1%prior 9

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 the 25 mph speed zone increased from 6 incidents in May 2024 to 7 incidents in May 2025. Crashes in the 30 mph speed zone remained constant at 4 incidents across both periods. A new crash occurred in the 20 mph speed zone in May 2025, where none were reported in May 2024.

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: SWAMPSCOTT, MA
  • Total crash records analyzed: 12
  • Total persons involved: 24
  • Total vehicles involved: 19

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). "SWAMPSCOTT, 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/swampscott/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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Swampscott, MA Crash Report — May 2025 | ThatCarHitMe.com