Monthly Traffic Safety Analysis

30 CRASHES IN
EVERETT, MA
NOVEMBER 2024

All metrics benchmarked againstNovember 2023

In November 2024, Everett experienced 30 crashes, a 3.2% decrease from the 31 crashes recorded in November 2023. A notable shift includes the number of hit-and-run crashes, which doubled from 1 in the prior period to 2 in the current period.

30

-3.2%was 31

Total Crash Events

0

Persons Killed

7

Persons Injured

2

100.0%was 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

Overall, the number of crashes in Everett saw a slight decrease, falling by 3.2% from 31 crashes in November 2023 to 30 crashes in November 2024. The total number of injuries remained stable at 7 in both periods.

2

Hit-and-Run Crashes — November 2024

100.0% vs prior (1)

The number of hit-and-run crashes doubled from 1 incident in November 2023 to 2 incidents in November 2024. This change resulted in the hit-and-run crash rate increasing from 3.2% in the prior period to 6.7% in the current period, indicating an upward trend.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

7

Motorists Injured

Prior: 616.7%

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 temporal patterns of crashes showed shifts year-over-year. The peak day for crashes moved from Friday with 8 incidents in November 2023 to Saturday with 7 incidents in November 2024. Similarly, the peak crash hour shifted from 8 AM with 5 crashes in November 2023 to 3 PM with 3 crashes in November 2024.

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

Fatalities remained at 0 in both November 2023 and November 2024, with no fatal crashes reported in either period. Minor injury crashes decreased from 6 incidents (19.4% share) in the prior period to 2 incidents (6.7% share) in the current period. Meanwhile, possible injury crashes increased from 1 incident (3.2% share) to 4 incidents (13.3% share) year-over-year.

Outcome by Severity (Crash Events)

Minor Injury2minor injury crashes6.7%
-66.7%prior 6
Possible Injury4possible injury crashes13.3%
300.0%prior 1
No Injury23no injury crashes76.7%
0.0%prior 23

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

The leading contributing factor, 'Disregarded traffic signs, signals, road markings,' decreased from 5 incidents in November 2023 to 4 incidents in November 2024. Factors such as 'Failed to yield right of way,' 'Followed too closely,' and 'No improper driving' each increased by 1 incident, rising from 3 to 4 incidents year-over-year. 'Inattention' also increased from 1 incident to 2 incidents between the two periods.

Officer-Reported Primary Contributing Cause

Failed to yield right of way4 (13.3%)
Followed too closely4 (13.3%)
Disregarded traffic signs, signals, road markings4 (13.3%)-20.0%prior 5
No improper driving4 (13.3%)
Inattention2 (6.7%)
Failure to keep in proper lane or running off road1 (3.3%)
Fatigued/asleep1 (3.3%)
Visibility obstructed1 (3.3%)

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

Crashes on dry road surfaces remained consistent with 27 incidents in both November 2023 and November 2024. Incidents occurring in daylight conditions decreased from 18 in the prior period to 15 in the current period, while crashes in dark-lighted roadway conditions held steady at 12. Crashes during rainy conditions saw a slight decrease, from 4 incidents in November 2023 to 3 incidents in November 2024.

Weather

Clear/Clear21 (70.0%)
90.9%prior 11
Clear6 (20.0%)
-57.1%prior 14
Rain/Rain2 (6.7%)
Rain1 (3.3%)

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

Lighting

Daylight15 (50.0%)
-16.7%prior 18
Dark - lighted roadway12 (40.0%)
0.0%prior 12
Dawn1 (3.3%)
Dusk1 (3.3%)
Other1 (3.3%)

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

Road Surface

Dry27 (90.0%)
0.0%prior 27
Wet3 (10.0%)

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

Vehicles & Demographics

The leading vehicle make involved in crashes, Toyota, increased from 13 incidents in November 2023 to 16 in November 2024. Honda vehicles saw a significant increase, rising from 6 incidents to 13 incidents year-over-year. Regarding person demographics, the 21-25 age group showed the largest increase, from 8 persons in the prior period to 13 in the current period, while the 16-20 age group decreased from 8 to 5 persons.

Top Vehicle Makes (63 vehicles)

1
TOYOTA16 (25.4%)
23.1%prior 13
2
HONDA13 (20.6%)
116.7%prior 6
3
NISSAN7 (11.1%)
4
FORD7 (11.1%)
5
CHEVROLET5 (7.9%)
6
MAZDA1 (1.6%)
7
MERCEDES-BENZ1 (1.6%)
8
NFLY1 (1.6%)
9
PETERBILT1 (1.6%)
10
SUBARU1 (1.6%)

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

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

Sex Distribution (64 persons with recorded sex)

Male45 (70.3%)
21.6%prior 37
Female19 (29.7%)
-17.4%prior 23

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 25 mph speed zones increased from 16 incidents in November 2023 to 18 incidents in November 2024. Conversely, crashes in 35 mph zones decreased from 12 incidents to 8 incidents year-over-year. The number of crashes in 30 mph zones increased from 1 to 2, and no fatal crashes were recorded across any speed zone in either period.

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: EVERETT, MA
  • Total crash records analyzed: 30
  • Total persons involved: 77
  • Total vehicles involved: 63

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). "EVERETT, 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/everett/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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Everett, MA Crash Report — November 2024 | ThatCarHitMe.com