Monthly Traffic Safety Analysis

44 CRASHES IN
STONEHAM, MA
NOVEMBER 2024

All metrics benchmarked againstNovember 2023

Total crashes in Stoneham, MA decreased by 12% year-over-year, from 50 crashes in November 2023 to 44 crashes in November 2024. Despite the overall reduction in crashes, incidents attributed to speeding, specifically 'Driving too fast for conditions', saw a notable increase from 0 crashes to 3 crashes. Fatalities remained at 0 in both periods, while total injuries slightly decreased from 18 to 17.

44

-12.0%was 50

Total Crash Events

0

Persons Killed

17

-5.6%was 18

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a decrease in crash activity, with total crashes falling by 12% from 50 to 44. Total injuries also saw a slight reduction, decreasing from 18 to 17. The number of fatal crashes remained stable at 0 for both November 2023 and November 2024.

1

Hit-and-Run Crashes — November 2024

0.0% vs prior (1)

The number of hit-and-run crashes remained constant at 1 incident in both November 2023 and November 2024. However, the hit-and-run rate slightly increased from 2% to 2.3% due to a decrease in the overall number of crashes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

17

Motorists Injured

Prior: 18-5.6%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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 11 incidents in November 2023 to Tuesday with 9 incidents in November 2024. Similarly, the peak crash hour moved from 7 AM with 6 crashes in the prior period to 3 PM with 7 crashes in the current period. This suggests a shift in the most frequent times and days for crash occurrences.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at 0 in both November 2023 and November 2024. However, serious injury crashes (Severity A) increased from 0 in the prior period to 2 in the current period. Minor injury crashes (Severity B) decreased from 13 to 6, while possible injury crashes (Severity C) increased from 1 to 3.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes4.5%
Minor Injury6minor injury crashes13.6%
-53.8%prior 13
Possible Injury3possible injury crashes6.8%
200.0%prior 1
No Injury32no injury crashes72.7%
-11.1%prior 36

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Most severe injury per crash record

Top Contributing Factors

Contributing factors showed several shifts year-over-year. Crashes attributed to 'Followed too closely' decreased by 3 incidents, from 9 to 6. Conversely, 'Driving too fast for conditions' increased by 3 incidents, from 0 to 3, and 'Inattention' increased by 1 incident, from 5 to 6. 'Failed to yield right of way' decreased by 3 incidents, from 4 to 1.

Officer-Reported Primary Contributing Cause

No improper driving11 (25%)0.0%prior 11
Inattention6 (13.6%)20.0%prior 5
Followed too closely6 (13.6%)-33.3%prior 9
Distracted3 (6.8%)
Driving too fast for conditions3 (6.8%)
Failure to keep in proper lane or running off road2 (4.5%)
Other improper action1 (2.3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (2.3%)
Visibility obstructed1 (2.3%)
Failed to yield right of way1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a shift in crash conditions, with crashes occurring in 'Clear' weather decreasing from 45 to 27. Crashes in 'Rain' conditions increased from 0 to 5, and 'Wet' road surfaces increased from 2 to 8. Crashes occurring during 'Daylight' decreased from 33 to 27, while those in 'Dark - lighted roadway' conditions increased from 13 to 15.

Weather

Clear27 (62.8%)
-40.0%prior 45
Rain5 (11.6%)
Clear/Clear5 (11.6%)
Rain/Rain3 (7.0%)
Cloudy/Cloudy1 (2.3%)
Cloudy1 (2.3%)
Clear/Cloudy1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Weather condition at time of crash

Lighting

Daylight27 (62.8%)
-18.2%prior 33
Dark - lighted roadway15 (34.9%)
15.4%prior 13
Dusk1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Lighting condition field

Road Surface

Dry35 (81.4%)
-27.1%prior 48
Wet8 (18.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 101 to 92 year-over-year. While TOYOTA remained the top vehicle make involved in crashes with 19 incidents in both periods, HONDA involvement decreased from 15 to 11. The 45-54 age group saw an increase in persons involved in crashes, rising from 9 to 16, while most other age groups experienced decreases.

Top Vehicle Makes (92 vehicles)

1
TOYOTA19 (20.7%)
0.0%prior 19
2
HONDA11 (12%)
-26.7%prior 15
3
FORD9 (9.8%)
28.6%prior 7
4
SUBARU6 (6.5%)
5
JEEP5 (5.4%)
0.0%prior 5
6
CHEVROLET5 (5.4%)
-44.4%prior 9
7
LEXUS4 (4.3%)
8
RAM3 (3.3%)
9
VOLKSWAGEN3 (3.3%)
10
GMC3 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Vehicle unit records

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

Sex Distribution (104 persons with recorded sex)

Male57 (54.8%)
-21.9%prior 73
Female47 (45.2%)
-6.0%prior 50

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed zone decreased by 6, from 21 in November 2023 to 15 in November 2024. Conversely, crashes in the 65 mph speed zone increased by 1, from 12 to 13. All speed zones reported 0 fatal crashes in both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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: 2024-11-01 through 2024-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-11-01 through 2024-11-30 (30 days)
  • Geographic scope: STONEHAM, MA
  • Total crash records analyzed: 44
  • Total persons involved: 108
  • Total vehicles involved: 92

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 2024." Published June 21, 2026. Reporting period: 2024-11-01 to 2024-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/stoneham/november-2024-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 2024 | ThatCarHitMe.com