Monthly Traffic Safety Analysis

34 CRASHES IN
STONEHAM, MA
DECEMBER 2024

All metrics benchmarked againstDecember 2023

Total crashes in STONEHAM decreased by 5.6%, from 36 in December 2023 to 34 in December 2024. This period saw a notable reduction in fatalities, with 0 recorded in December 2024 compared to 1 in December 2023. Total injuries also decreased, falling from 12 to 8 year-over-year.

34

-5.6%was 36

Total Crash Events

0

-100.0%was 1

Persons Killed

8

-33.3%was 12

Persons Injured

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 · 2024-12-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in STONEHAM decreased year-over-year, with total crashes falling from 36 to 34, a 5.6% reduction. Fatalities declined from 1 to 0, and total injuries decreased from 12 to 8. This indicates a downward trend in both crash frequency and severity.

2

Hit-and-Run Crashes — December 2024

0.0% vs prior (2)

The number of hit-and-run crashes remained constant at 2 for both December 2023 and December 2024. However, due to a slight decrease in total crashes, the hit-and-run rate increased marginally from 5.6% to 5.9%.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1-100.0%

8

Motorists Injured

Prior: 12-33.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · 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 9 crashes in December 2023, to Friday, with 8 crashes in December 2024. The peak hour also shifted, moving from 8 AM (4 crashes) in the prior period to 9 AM (5 crashes) in the current period. Crashes on Mondays remained consistent at 7 for both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased from 1 (2.8% of crashes) in December 2023 to 0 in December 2024. Serious injuries (severity 'A') increased from 0 to 1 crash, representing 2.9% of current crashes. Possible injury crashes (severity 'C') decreased from 7 (19.4%) to 5 (14.7%) year-over-year.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.9%
Minor Injury2minor injury crashes5.9%
0.0%prior 2
Possible Injury5possible injury crashes14.7%
-28.6%prior 7
No Injury25no injury crashes73.5%
-3.8%prior 26

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

The number of crashes where 'No improper driving' was cited decreased from 14 to 6. 'Followed too closely' crashes decreased from 5 to 4, while 'Failed to yield right of way' crashes increased from 3 to 4. 'Failure to keep in proper lane or running off road' became a more prominent factor, accounting for 4 crashes in December 2024 compared to its lower incidence in the prior period's top factors.

Officer-Reported Primary Contributing Cause

No improper driving6 (17.6%)-57.1%prior 14
Failure to keep in proper lane or running off road4 (11.8%)
Followed too closely4 (11.8%)-20.0%prior 5
Failed to yield right of way4 (11.8%)
Other improper action2 (5.9%)
Driving too fast for conditions2 (5.9%)
Disregarded traffic signs, signals, road markings1 (2.9%)
Inattention1 (2.9%)
Emotional1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions (Clear or Clear/Clear) decreased from 28 in December 2023 to 15 in December 2024. Concurrently, crashes on wet road surfaces increased from 6 to 9, and crashes on snowy road surfaces increased from 0 to 5. Crashes occurring in 'Dark - lighted roadway' conditions decreased from 15 to 7.

Weather

Clear9 (26.5%)
-64.0%prior 25
Clear/Clear6 (17.6%)
Snow3 (8.8%)
Cloudy3 (8.8%)
Snow/Snow2 (5.9%)
Cloudy/Cloudy2 (5.9%)
Rain2 (5.9%)
Fog, smog, smoke/Unknown1 (2.9%)
Clear/Cloudy1 (2.9%)
Rain/Rain1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight20 (58.8%)
-4.8%prior 21
Dark - lighted roadway7 (20.6%)
-53.3%prior 15
Dark - roadway not lighted3 (8.8%)
Dark - unknown roadway lighting2 (5.9%)
Dawn1 (2.9%)
Dusk1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry19 (55.9%)
-34.5%prior 29
Wet9 (26.5%)
50.0%prior 6
Snow5 (14.7%)
Ice1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 67 to 71 year-over-year. Toyota became the top vehicle make involved, increasing from 10 to 13, while Ford decreased from 9 to 8. Among persons involved, the 21-25 age group saw a notable increase from 7 to 15, while the 26-34 age group decreased from 20 to 13, and the 65+ age group decreased from 13 to 7.

Top Vehicle Makes (71 vehicles)

1
TOYOTA13 (18.3%)
30.0%prior 10
2
HONDA12 (16.9%)
9.1%prior 11
3
FORD8 (11.3%)
-11.1%prior 9
4
NISSAN4 (5.6%)
-42.9%prior 7
5
JEEP4 (5.6%)
6
HYUNDAI3 (4.2%)
-40.0%prior 5
7
VOLVO2 (2.8%)
8
LEXUS2 (2.8%)
9
CHEVROLET2 (2.8%)
10
RAM2 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (76 persons with recorded sex)

Male47 (61.8%)
17.5%prior 40
Female29 (38.2%)
-19.4%prior 36

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 MPH speed zones decreased from 16 to 12 year-over-year. Conversely, crashes in 35 MPH speed zones increased from 3 to 5. The prior period recorded 1 fatal crash in a 65 MPH zone, whereas no fatal crashes were reported in any speed zone in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · 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: 2024-12-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-12-01 through 2024-12-31 (31 days)
  • Geographic scope: STONEHAM, MA
  • Total crash records analyzed: 34
  • Total persons involved: 90
  • Total vehicles involved: 71

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: December 2024." Published June 21, 2026. Reporting period: 2024-12-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/stoneham/december-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 — December 2024 | ThatCarHitMe.com