Monthly Traffic Safety Analysis

28 CRASHES IN
SOMERSET, MA
APRIL 2025

All metrics benchmarked againstApril 2024

Total crashes in Somerset decreased from 37 in April 2024 to 28 in April 2025, representing a 24.3% reduction year-over-year. The most notable year-over-year shift was a significant decrease in crashes attributed to "Failed to yield right of way," which dropped from 9 in the prior period to 3 in the current period. This indicates an overall improvement in crash frequency for the month.

28

-24.3%was 37

Total Crash Events

0

Persons Killed

10

-9.1%was 11

Persons Injured

3

50.0%was 2

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 · 2025-04-01 to 2025-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in Somerset decreased by 24.3% year-over-year, from 37 crashes in April 2024 to 28 crashes in April 2025. This indicates a notable downward trend in crash incidents for the month. Fatalities remained at zero for both periods.

3

Hit-and-Run Crashes — April 2025

50.0% vs prior (2)

Hit-and-run crashes increased from 2 in April 2024 to 3 in April 2025. Consequently, the hit-and-run rate rose from 5.4% in the prior period to 10.7% in the current period. This indicates an upward trend in the proportion of crashes involving a hit-and-run incident.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 0%

9

Motorists Injured

Prior: 11-18.2%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · 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 Saturday with 10 crashes in April 2024 to Friday with 7 crashes in April 2025. The peak hour also changed from 4 p.m. with 6 crashes in April 2024 to 12 p.m. with 6 crashes in April 2025. This suggests a shift in when the highest number of crashes occur within the week and day.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While both periods reported zero fatalities, the current period saw 2 serious injury crashes (code A), which were not present in the prior period. The number of minor injury crashes decreased from 7 in April 2024 to 6 in April 2025, and possible injury crashes decreased from 2 to 1. Total injuries decreased from 11 in the prior period to 10 in the current period.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes7.1%
Minor Injury6minor injury crashes21.4%
-14.3%prior 7
Possible Injury1possible injury crashes3.6%
-50.0%prior 2
No Injury18no injury crashes64.3%
-33.3%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "Failed to yield right of way" decreased from 9 crashes in the prior period to 3 crashes in the current period, a reduction of 6 crashes. Conversely, "No improper driving" as a contributing factor increased from 5 crashes in the prior period to 10 crashes in the current period, an increase of 5 crashes. The number of "Inattention" crashes decreased from 5 to 3 year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving10 (35.7%)100.0%prior 5
Failed to yield right of way3 (10.7%)-66.7%prior 9
Failure to keep in proper lane or running off road3 (10.7%)
Inattention3 (10.7%)-40.0%prior 5
Followed too closely2 (7.1%)
Made an improper turn2 (7.1%)
Driving too fast for conditions2 (7.1%)
Over-correcting/over-steering1 (3.6%)
Distracted1 (3.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The number of crashes occurring in clear weather conditions decreased from 30 in April 2024 to 16 in April 2025, while crashes in rainy conditions increased from 1 to 5. Crashes on dry road surfaces decreased from 32 to 20, whereas crashes on wet road surfaces increased from 4 to 6, and 1 crash occurred on a road with standing water in the current period. This indicates a shift towards more crashes in adverse weather and road surface conditions.

Weather

Clear16 (59.3%)
-46.7%prior 30
Clear/Clear5 (18.5%)
Rain2 (7.4%)
Cloudy/Rain1 (3.7%)
Cloudy1 (3.7%)
Rain/Cloudy1 (3.7%)
Rain/Rain1 (3.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Weather condition at time of crash

Lighting

Daylight23 (85.2%)
-23.3%prior 30
Dark - lighted roadway2 (7.4%)
Dark - roadway not lighted1 (3.7%)
Dawn1 (3.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Lighting condition field

Road Surface

Dry20 (74.1%)
-37.5%prior 32
Wet6 (22.2%)
Water (standing, moving)1 (3.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (47 vehicles)

1
TOYOTA9 (19.1%)
-18.2%prior 11
2
HONDA5 (10.6%)
-44.4%prior 9
3
CHEVROLET5 (10.6%)
4
FORD4 (8.5%)
5
HYUNDAI4 (8.5%)
-33.3%prior 6
6
BMW2 (4.3%)
7
NISSAN2 (4.3%)
8
HD1 (2.1%)
9
BUIC1 (2.1%)
10
ISU1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Vehicle unit records

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

Sex Distribution (49 persons with recorded sex)

Male31 (63.3%)
-24.4%prior 41
Female18 (36.7%)
-35.7%prior 28

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 30 mph zones decreased from 14 in April 2024 to 10 in April 2025. Conversely, crashes in 65 mph zones increased from 2 to 5, and crashes in 40 mph zones increased from 3 to 5. No fatal crashes were reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · 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: 2025-04-01 through 2025-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-04-01 through 2025-04-30 (30 days)
  • Geographic scope: SOMERSET, MA
  • Total crash records analyzed: 28
  • Total persons involved: 57
  • Total vehicles involved: 47

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). "SOMERSET, MA Crash Intelligence Report: April 2025." Published June 21, 2026. Reporting period: 2025-04-01 to 2025-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/somerset/april-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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Somerset, MA Crash Report — April 2025 | ThatCarHitMe.com