Monthly Traffic Safety Analysis

30 CRASHES IN
STONEHAM, MA
NOVEMBER 2025

All metrics benchmarked againstNovember 2024

In November 2025, STONEHAM experienced 30 crashes, a 31.8% decrease from the 44 crashes recorded in November 2024. Despite the overall reduction in crashes, there was one fatality in November 2025 compared to zero fatalities in the prior year.

30

-31.8%was 44

Total Crash Events

1

Persons Killed

12

-29.4%was 17

Persons Injured

4

300.0%was 1

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a significant decrease in total crashes in November 2025 compared to November 2024. Crashes fell by 14 incidents, representing a 31.8% reduction year-over-year.

4

Hit-and-Run Crashes — November 2025

300.0% vs prior (1)

Hit-and-run crashes increased significantly from 1 incident in November 2024 to 4 incidents in November 2025. This resulted in a substantial increase in the hit-and-run rate, rising from 2.3% of total crashes in the prior period to 13.3% in the current period, indicating an upward trend.

Vulnerable Road User Casualties

1

Cyclists Killed

Prior: 0%

0

Motorists Killed

Prior: 00.0%

0

Cyclists Injured

Prior: 00.0%

12

Motorists Injured

Prior: 17-29.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed shifts year-over-year. In November 2025, the peak day for crashes was Friday with 6 incidents, whereas in November 2024, Tuesday was the peak with 9 crashes. The peak hour also shifted from 3 PM with 7 crashes in the prior period to 4 PM with 6 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The current period saw one fatality, an increase from zero in the prior period. Total injuries decreased from 17 in November 2024 to 12 in November 2025. Specifically, serious injuries decreased from 2 to 1, minor injuries decreased from 8 to 4, and possible injuries remained constant at 7 year-over-year.

Outcome by Severity (Crash Events)

Fatal1fatal crashes3.3%
Minor Injury3minor injury crashes10%
-50.0%prior 6
Possible Injury5possible injury crashes16.7%
66.7%prior 3
No Injury21no injury crashes70%
-34.4%prior 32

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Most severe injury per crash record

Top Contributing Factors

Analysis of contributing factors reveals shifts in crash causation. Crashes attributed to 'Followed too closely' increased from 6 in November 2024 to 7 in November 2025, representing a 16.7% increase in count. Conversely, 'No improper driving' as a factor decreased significantly from 11 crashes in the prior period to 5 in the current period, a 54.5% decrease in count. 'Failed to yield right of way' saw a substantial increase from 1 crash to 4 crashes, a 300% increase in count, while 'Inattention' decreased from 6 crashes to 1 crash.

Officer-Reported Primary Contributing Cause

Followed too closely7 (23.3%)16.7%prior 6
No improper driving5 (16.7%)-54.5%prior 11
Failed to yield right of way4 (13.3%)
Made an improper turn2 (6.7%)
Inattention1 (3.3%)-83.3%prior 6
Failure to keep in proper lane or running off road1 (3.3%)
Glare1 (3.3%)
Distracted1 (3.3%)
Other improper action1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Road conditions remained predominantly dry in both periods, with 27 crashes on dry roads in November 2025 compared to 35 in November 2024. Crashes on wet roads decreased from 8 in the prior period to 3 in the current period. Under lighting conditions, daylight crashes decreased from 27 to 12, while crashes in dark-lighted roadway conditions decreased from 15 to 12.

Weather

Clear12 (40.0%)
-55.6%prior 27
Clear/Clear11 (36.7%)
120.0%prior 5
Cloudy/Cloudy2 (6.7%)
Cloudy1 (3.3%)
Clear/Cloudy1 (3.3%)
Fog, smog, smoke/Cloudy1 (3.3%)
Rain/Cloudy1 (3.3%)
Rain/Rain1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Weather condition at time of crash

Lighting

Dark - lighted roadway12 (40.0%)
-20.0%prior 15
Daylight12 (40.0%)
-55.6%prior 27
Dusk5 (16.7%)
Dark - roadway not lighted1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Lighting condition field

Road Surface

Dry27 (90.0%)
-22.9%prior 35
Wet3 (10.0%)
-62.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 92 in November 2024 to 64 in November 2025. Toyota remained the top make involved in crashes, though its count decreased from 19 to 13. Honda's involvement decreased from 11 to 8, while Nissan's involvement increased from 3 to 11, moving from a lower rank in the prior period to the second highest in the current period.

Top Vehicle Makes (64 vehicles)

1
TOYOTA13 (20.3%)
-31.6%prior 19
2
NISSAN11 (17.2%)
3
HONDA8 (12.5%)
-27.3%prior 11
4
FORD5 (7.8%)
-44.4%prior 9
5
JEEP5 (7.8%)
0.0%prior 5
6
SUBARU3 (4.7%)
-50.0%prior 6
7
HYUNDAI2 (3.1%)
8
BMW2 (3.1%)
9
KIA1 (1.6%)
10
MERCEDES-BENZ1 (1.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Vehicle unit records

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

Sex Distribution (58 persons with recorded sex)

Female32 (55.2%)
-31.9%prior 47
Male26 (44.8%)
-54.4%prior 57

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 MPH speed zones decreased from 15 in November 2024 to 9 in November 2025, with one fatal crash occurring in this zone in the current period compared to none in the prior period. Crashes in 65 MPH zones also decreased from 13 to 7. The number of crashes in 30 MPH zones remained constant at 7 for both periods.

Fatal crashes by zone: 25 mph: 1 of 9 (11.111%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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: 2025-11-01 through 2025-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-11-01 through 2025-11-30 (30 days)
  • Geographic scope: STONEHAM, MA
  • Total crash records analyzed: 30
  • Total persons involved: 73
  • Total vehicles involved: 64

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). "STONEHAM, MA Crash Intelligence Report: November 2025." Published June 21, 2026. Reporting period: 2025-11-01 to 2025-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/stoneham/november-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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Stoneham, MA Crash Report — November 2025 | ThatCarHitMe.com