Monthly Traffic Safety Analysis

45 CRASHES IN
GLOUCESTER, MA
FEBRUARY 2025

All metrics benchmarked againstFebruary 2024

In February 2025, Gloucester experienced 45 total crashes, an increase from 32 crashes in February 2024, representing a 40.6% rise. The most notable year-over-year shift was the overall increase in total crashes, despite a decrease in total injuries from 10 to 6. Fatalities remained at zero in both periods.

45

40.6%was 32

Total Crash Events

0

Persons Killed

6

-40.0%was 10

Persons Injured

3

-25.0%was 4

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 · 2025-02-01 to 2025-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a significant increase in total crashes, rising from 32 in February 2024 to 45 in February 2025, which is a 40.6% increase. Despite this rise in crash incidents, total injuries decreased by 40%, from 10 to 6, suggesting a shift towards less severe outcomes per crash.

3

Hit-and-Run Crashes — February 2025

-25.0% vs prior (4)

Hit-and-run crashes decreased from 4 in February 2024 to 3 in February 2025. Consequently, the hit-and-run rate also saw a decline, dropping from 12.5% in the prior period to 6.7% in the current period, indicating a downward trend.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

6

Motorists Injured

Prior: 10-40.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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 8 crashes in February 2024 to Thursday with 10 crashes in February 2025. The peak hour for crashes also shifted, moving from 3 PM in February 2024 to 4 PM in February 2025, with both periods recording 5 crashes at their respective peak hours.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both February 2024 and February 2025. Total injuries decreased from 10 in the prior period to 6 in the current period. The proportion of minor injury crashes increased from 6.3% (2 crashes) in February 2024 to 13.3% (6 crashes) in February 2025, while possible injury crashes (4 crashes, 12.5%) observed in the prior period were not present in the current period.

Outcome by Severity (Crash Events)

Minor Injury6minor injury crashes13.3%
200.0%prior 2
No Injury38no injury crashes84.4%
58.3%prior 24

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'No improper driving' increased by 10, from 13 in February 2024 to 23 in February 2025. 'Inattention' remained constant at 3 crashes in both periods. 'Failed to yield right of way' crashes increased by 1, from 1 to 2, and 'Driving too fast for conditions' increased from 0 in the prior period to 4 in the current period.

Officer-Reported Primary Contributing Cause

No improper driving23 (51.1%)76.9%prior 13
Driving too fast for conditions4 (8.9%)
Inattention3 (6.7%)
Failed to yield right of way2 (4.4%)
Physical impairment1 (2.2%)
Visibility obstructed1 (2.2%)
Other improper action1 (2.2%)
Made an improper turn1 (2.2%)
Followed too closely1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions slightly increased from 21 to 23 year-over-year. Snow-related crashes saw a notable increase from 1 (Sleet, hail/Snow) in February 2024 to 7 (Snow) in February 2025. Crashes on wet road surfaces also increased from 0 to 7, while crashes on dry roads decreased from 31 to 29.

Weather

Clear23 (51.1%)
9.5%prior 21
Snow7 (15.6%)
Cloudy6 (13.3%)
Cloudy/Rain2 (4.4%)
Clear/Unknown2 (4.4%)
Sleet, hail (freezing rain or drizzle)1 (2.2%)
Sleet, hail (freezing rain or drizzle)/Rain1 (2.2%)
Clear/Clear1 (2.2%)
Cloudy/Clear1 (2.2%)
Rain/Snow1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Weather condition at time of crash

Lighting

Daylight32 (71.1%)
45.5%prior 22
Dark - lighted roadway9 (20.0%)
Dawn2 (4.4%)
Dark - roadway not lighted1 (2.2%)
Other1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Lighting condition field

Road Surface

Dry29 (64.4%)
-6.5%prior 31
Wet7 (15.6%)
Snow5 (11.1%)
Ice2 (4.4%)
Slush2 (4.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 61 in February 2024 to 82 in February 2025. TOYOTA vehicles involved in crashes increased from 7 to 13, while HONDA increased from 9 to 12, and FORD increased from 6 to 9. The 26-34 age group saw a substantial increase in person involvement, from 4 to 15, while the 65+ age group decreased from 10 to 7 persons.

Top Vehicle Makes (82 vehicles)

1
TOYOTA13 (15.9%)
85.7%prior 7
2
HONDA12 (14.6%)
33.3%prior 9
3
FORD9 (11%)
50.0%prior 6
4
CHEVROLET7 (8.5%)
5
JEEP6 (7.3%)
20.0%prior 5
6
NISSAN4 (4.9%)
7
HYUNDAI4 (4.9%)
8
SUBARU3 (3.7%)
-50.0%prior 6
9
MAZDA3 (3.7%)
10
MERCEDES-BENZ2 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Vehicle unit records

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

Sex Distribution (72 persons with recorded sex)

Male39 (54.2%)
11.4%prior 35
Female33 (45.8%)
94.1%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph zones increased from 15 in February 2024 to 22 in February 2025. The number of crashes in 20 mph zones remained constant at 2, as did crashes in 55 mph zones, which stayed at 4. Fatal rates remained at 0 in all speed zones for both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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: 2025-02-01 through 2025-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-02-01 through 2025-02-28 (28 days)
  • Geographic scope: GLOUCESTER, MA
  • Total crash records analyzed: 45
  • Total persons involved: 89
  • Total vehicles involved: 82

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). "GLOUCESTER, MA Crash Intelligence Report: February 2025." Published June 21, 2026. Reporting period: 2025-02-01 to 2025-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/gloucester/february-2025-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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Gloucester, MA Crash Report — February 2025 | ThatCarHitMe.com