ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GLOUCESTER, MA · DECEMBER 2025
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/gloucester/december-2025-report
Monthly Traffic Safety Analysis
30 CRASHES IN
GLOUCESTER, MA
DECEMBER 2025
In December 2025, Gloucester recorded 30 total crashes, a decrease of 28.57% from the 42 crashes reported in December 2024. The most significant year-over-year shift was the increase in total fatalities, from 0 in December 2024 to 1 in December 2025.
30
▼ -28.6%was 42
Total Crash Events
1
Persons Killed
5
▼ -28.6%was 7
Persons Injured
1
▼ -80.0%was 5
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in Gloucester decreased by 28.57% from 42 crashes in December 2024 to 30 crashes in December 2025. Despite this reduction in overall incidents, total fatalities increased from 0 to 1, while total injuries decreased from 7 to 5.
1
Hit-and-Run Crashes — December 2025
▼ -80.0% vs prior (5)
The number of hit-and-run crashes decreased from 5 in December 2024 to 1 in December 2025. Correspondingly, the hit-and-run rate decreased from 11.9% of total crashes in the prior period to 3.3% in the current period.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
4
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · 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 Monday with 10 crashes in December 2024 to Tuesday with 12 crashes in December 2025. The peak hour for crashes shifted from 5 PM with 5 crashes in December 2024 to 3 PM, also with 5 crashes, in December 2025.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The city experienced one fatal crash in December 2025, compared to zero fatal crashes in December 2024. Minor injury crashes remained at 3 in both periods, though their share of total crashes increased from 7.1% to 10% due to the overall decrease in incidents. Crashes resulting in no injury decreased from 32 to 24.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
The number of crashes where 'No improper driving' was a factor decreased from 17 in December 2024 to 11 in December 2025. Crashes attributed to 'Failed to yield right of way' saw a notable decrease from 5 to 1. Conversely, 'Over-correcting/over-steering' incidents increased from 1 to 2, and 'Glare' appeared as a factor in 2 crashes in December 2025, whereas it was not among the top factors in December 2024.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions significantly decreased from 28 in December 2024 to 12 in December 2025, while crashes in 'Snow/Snow' conditions appeared in December 2025 with 2 incidents. Incidents during 'Dark - lighted roadway' conditions saw a substantial drop from 13 to 2, whereas crashes during 'Dawn' increased from 1 to 5. Road surface conditions categorized as 'Dry' decreased from 34 crashes to 17, with the current period also reporting crashes on 'Ice' (3), 'Snow' (3), and 'Slush' (1) surfaces, which were not present in the prior period's top conditions.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 81 in December 2024 to 55 in December 2025. While FORD vehicles involved in crashes increased from 8 to 10, TOYOTA vehicles decreased from 10 to 3, and CHEVROLET vehicles decreased from 7 to 4. Among persons involved, the 26-34 age group saw an increase from 8 to 12, while the 35-44 age group decreased from 15 to 11.
Top Vehicle Makes (55 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Vehicle unit records
5 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (61 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 25 MPH speed zones decreased significantly from 20 in December 2024 to 4 in December 2025. Conversely, crashes in 55 MPH speed zones doubled from 3 to 6. Both periods reported no fatal crashes within any recorded speed zone.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · 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: 2025-12-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-12-01 through 2025-12-31 (31 days)
- Geographic scope: GLOUCESTER, MA
- Total crash records analyzed: 30
- Total persons involved: 65
- Total vehicles involved: 55
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: December 2025." Published June 21, 2026. Reporting period: 2025-12-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/gloucester/december-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-12-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved