Monthly Traffic Safety Analysis

26 CRASHES IN
EVERETT, MA
SEPTEMBER 2024

All metrics benchmarked againstSeptember 2023

Total crashes in Everett increased by 52.9% year-over-year, rising from 17 crashes in September 2023 to 26 crashes in September 2024. This notable increase in overall crash incidents was accompanied by a rise in total injuries from 7 to 11 over the same period. Fatalities remained at 0 in both periods.

26

52.9%was 17

Total Crash Events

0

Persons Killed

11

57.1%was 7

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 · 2024-09-01 to 2024-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a significant increase in crash activity year-over-year, with total crashes rising from 17 to 26, representing a 52.9% increase. Total injuries also increased from 7 to 11, marking a 57.1% rise. Fatalities remained stable at 0 in both periods.

2

Hit-and-Run Crashes — September 2024

7.7% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

10

Motorists Injured

Prior: 742.9%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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 Tuesday with 6 crashes in September 2023 to Sunday with 6 crashes in September 2024. Similarly, the peak hour for crashes changed from 1 PM with 3 crashes in the prior period to 10 PM with 3 crashes in the current period. Both peak day and peak hour maintained the same number of crashes but occurred on different days and times.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Total fatalities remained at 0 in both September 2023 and September 2024. Total injuries increased from 7 in the prior period to 11 in the current period. The proportion of minor injuries decreased from 29.4% to 26.9% of total crashes, while possible injuries increased from 5.9% to 11.5% of total crashes.

Outcome by Severity (Crash Events)

Minor Injury7minor injury crashes26.9%
40.0%prior 5
Possible Injury3possible injury crashes11.5%
200.0%prior 1
No Injury15no injury crashes57.7%
36.4%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Most severe injury per crash record

Top Contributing Factors

"Followed too closely" increased from 2 crashes in the prior period to 3 crashes in the current period, representing a 50% increase in count. "No improper driving" decreased from 4 crashes to 3 crashes, a 25% decrease in count. "Disregarded traffic signs, signals, road markings" decreased from 3 crashes to 2 crashes, a 33.3% decrease in count. "Failed to yield right of way" increased from 1 crash to 2 crashes, a 100% increase in count. "Inattention" appeared in the current period with 2 crashes, while it was not present in the prior period.

Officer-Reported Primary Contributing Cause

Followed too closely3 (11.5%)
No improper driving3 (11.5%)
Disregarded traffic signs, signals, road markings2 (7.7%)
Inattention2 (7.7%)
Failed to yield right of way2 (7.7%)
Failure to keep in proper lane or running off road1 (3.8%)
Emotional1 (3.8%)
Physical impairment1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions (Clear/Clear or Clear) increased from 10 in the prior period to 24 in the current period. Concurrently, crashes on dry road surfaces increased from 9 to 24. The number of crashes occurring on wet road surfaces decreased from 6 to 1, and crashes during rainy weather decreased from 5 to 0.

Weather

Clear/Clear13 (52.0%)
160.0%prior 5
Clear11 (44.0%)
120.0%prior 5
Cloudy/Cloudy1 (4.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Weather condition at time of crash

Lighting

Daylight14 (56.0%)
27.3%prior 11
Dark - lighted roadway8 (32.0%)
Dark - roadway not lighted1 (4.0%)
Dawn1 (4.0%)
Dusk1 (4.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Lighting condition field

Road Surface

Dry24 (96.0%)
166.7%prior 9
Wet1 (4.0%)
-83.3%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (54 vehicles)

1
HONDA13 (24.1%)
160.0%prior 5
2
TOYOTA8 (14.8%)
14.3%prior 7
3
FORD7 (13%)
-12.5%prior 8
4
CHEVROLET4 (7.4%)
5
NISSAN4 (7.4%)
6
SUBARU3 (5.6%)
7
KIA3 (5.6%)
8
MAZDA2 (3.7%)
9
VOLVO1 (1.9%)
10
BMW1 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Vehicle unit records

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

Sex Distribution (58 persons with recorded sex)

Male33 (56.9%)
32.0%prior 25
Female24 (41.4%)
50.0%prior 16
X / Unspecified1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph zones increased from 8 to 12, and in 35 mph zones from 5 to 9. The current period also recorded crashes in 15 mph (1 crash) and 20 mph (2 crashes) zones, which were not present in the prior period. All speed zones reported 0 fatalities in both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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: 2024-09-01 through 2024-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-09-01 through 2024-09-30 (30 days)
  • Geographic scope: EVERETT, MA
  • Total crash records analyzed: 26
  • Total persons involved: 67
  • Total vehicles involved: 54

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: September 2024." Published June 21, 2026. Reporting period: 2024-09-01 to 2024-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/everett/september-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 — September 2024 | ThatCarHitMe.com