Yearly Traffic Safety Analysis

431 CRASHES IN
STONEHAM, MA
2024

All metrics benchmarked against2023

In Stoneham, total traffic crashes increased by 6.7% from 404 in 2023 to 431 in 2024. During this period, the number of fatalities doubled from one to two, and total injuries rose by 28.4% from 116 to 149. The most significant shift was the increase in the count of crashes attributed to factors like 'Driving too fast for conditions' and 'Inattention', which grew by 143% and 40% respectively.

431

6.7%was 404

Total Crash Events

2

100.0%was 1

Persons Killed

149

28.4%was 116

Persons Injured

18

-14.3%was 21

Hit-and-Run Crashes

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 6 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crash trends in Stoneham show an increase year-over-year. Total crashes rose from 404 to 431, a 6.7% increase. This was accompanied by a more pronounced rise in severity, with total injuries increasing by 28.4% from 116 to 149 and fatalities doubling from 1 to 2.

18

Hit-and-Run Crashes — 2024

-14.3% vs prior (21)

Hit-and-run incidents showed a downward trend. The total number of hit-and-run crashes decreased from 21 in the prior year to 18 in the current year. This corresponds to a decrease in the hit-and-run rate, which fell from 5.2% of all crashes in 2023 to 4.2% in 2024.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

1

Motorists Killed

Prior: 10.0%

2

Pedestrians Injured

Prior: 20.0%

147

Motorists Injured

Prior: 11033.6%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between the two periods. The peak day for crashes moved from Tuesday (66 crashes) in the prior year to Friday (84 crashes) in the current year. Similarly, the peak hour for collisions shifted slightly earlier from the 3 PM hour in 2023 to the 2 PM hour in 2024.

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

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

Crash Severity Breakdown

The severity of crashes increased year-over-year. The number of fatal crashes doubled from 1 to 2, and the count of serious injury crashes also doubled from 5 to 10. Consequently, the proportion of crashes involving any injury (fatal, serious, minor, or possible) rose from 22.3% of all crashes in 2023 to 24.8% in 2024.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.5%
100.0%prior 1
Serious Injury10serious injury crashes2.3%
100.0%prior 5
Minor Injury63minor injury crashes14.6%
6.8%prior 59
Possible Injury34possible injury crashes7.9%
30.8%prior 26
No Injury316no injury crashes73.3%
1.6%prior 311

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

While 'Followed too closely' remained a leading factor, its crash count increased by 26% from 61 to 77 incidents. Other notable changes include a 143% increase in the count of crashes attributed to 'Driving too fast for conditions' (from 7 to 17) and a 100% increase in 'Distracted' driving crashes (from 8 to 16). Conversely, the number of crashes where 'No improper driving' was cited decreased by 40% from a count of 137 to 82.

Officer-Reported Primary Contributing Cause

No improper driving82 (19%)-40.1%prior 137
Followed too closely77 (17.9%)26.2%prior 61
Failed to yield right of way42 (9.7%)35.5%prior 31
Inattention35 (8.1%)40.0%prior 25
Other improper action18 (4.2%)63.6%prior 11
Driving too fast for conditions17 (3.9%)142.9%prior 7
Distracted16 (3.7%)100.0%prior 8
Failure to keep in proper lane or running off road16 (3.7%)-23.8%prior 21
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner11 (2.6%)57.1%prior 7
Exceeded authorized speed limit10 (2.3%)25.0%prior 8

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

Road & Environmental Conditions

Year-over-year, a greater number of crashes occurred during adverse weather and road conditions. Crashes in the rain increased from 25 to 33, and collisions on wet roads rose from 53 to 67. While the count of crashes on dry roads was identical at 345 for both periods, they represented a smaller share of the total in the current year (80.0%) compared to the prior year (85.4%).

Weather

Clear274 (63.9%)
-4.5%prior 287
Clear/Clear49 (11.4%)
16.7%prior 42
Rain33 (7.7%)
32.0%prior 25
Cloudy29 (6.8%)
70.6%prior 17
Snow8 (1.9%)
Rain/Cloudy5 (1.2%)
Snow/Snow4 (0.9%)
Cloudy/Rain4 (0.9%)
-20.0%prior 5
Rain/Rain4 (0.9%)
Sleet, hail (freezing rain or drizzle)4 (0.9%)

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

Lighting

Daylight310 (72.1%)
6.5%prior 291
Dark - lighted roadway103 (24.0%)
28.7%prior 80
Dark - roadway not lighted7 (1.6%)
-36.4%prior 11
Dusk4 (0.9%)
-76.5%prior 17
Dawn3 (0.7%)
Dark - unknown roadway lighting3 (0.7%)

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

Road Surface

Dry345 (80.2%)
0.0%prior 345
Wet67 (15.6%)
26.4%prior 53
Snow12 (2.8%)
140.0%prior 5
Ice3 (0.7%)
Slush3 (0.7%)

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

Vehicles & Demographics

The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—remained the same across both years, with Toyota involvement increasing from 122 to 171 vehicles. An analysis of person demographics shows a notable increase in crash involvement for individuals in the 45-54 age group, which grew from 107 people in the prior year to 137 in the current year. The total number of people involved in crashes increased from 961 to 1,052.

Top Vehicle Makes (881 vehicles)

1
TOYOTA171 (19.4%)
40.2%prior 122
2
HONDA135 (15.3%)
12.5%prior 120
3
FORD93 (10.6%)
12.0%prior 83
4
JEEP51 (5.8%)
30.8%prior 39
5
CHEVROLET47 (5.3%)
-9.6%prior 52
6
NISSAN47 (5.3%)
-4.1%prior 49
7
SUBARU27 (3.1%)
-3.6%prior 28
8
MAZDA22 (2.5%)
57.1%prior 14
9
LEXUS22 (2.5%)
83.3%prior 12
10
BMW21 (2.4%)
40.0%prior 15

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

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

Sex Distribution (982 persons with recorded sex)

Male541 (55.1%)
4.6%prior 517
Female441 (44.9%)
13.7%prior 388

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

Speed Limit Zones

Crash locations appeared to shift toward areas with higher speed limits. The number of crashes in 35 mph zones increased from 35 to 58, and collisions in 55 mph zones nearly doubled from 12 to 23. In contrast, crashes in 25 mph zones decreased from 161 to 143. The current period saw a fatal crash in a 15 mph zone, a speed zone that had no fatalities in the prior year.

Fatal crashes by zone: 15 mph: 1 of 2 (50%) · 65 mph: 1 of 119 (0.84%)

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

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: STONEHAM, MA
  • Total crash records analyzed: 431
  • Total persons involved: 1,052
  • Total vehicles involved: 881

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