ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GLOUCESTER, MA · JANUARY 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/january-2025-report
Monthly Traffic Safety Analysis
45 CRASHES IN
GLOUCESTER, MA
JANUARY 2025
In January 2025, Gloucester recorded 45 crashes, a 6.25% decrease compared to the 48 crashes in January 2024. Total injuries also saw a slight reduction, from 9 to 8. One notable shift was a 50% decrease in hit-and-run crashes, falling from 4 in the prior period to 2 in the current period.
45
▼ -6.3%was 48
Total Crash Events
0
Persons Killed
8
▼ -11.1%was 9
Persons Injured
2
▼ -50.0%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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for January 2025 in Gloucester indicates a slight downward trend compared to January 2024. Total crashes decreased by 6.25%, from 48 to 45, while total injuries also saw an 11.1% reduction, from 9 to 8. Fatalities remained at 0 in both periods, suggesting stable safety outcomes in terms of severe incidents.
2
Hit-and-Run Crashes — January 2025
▼ -50.0% vs prior (4)
Hit-and-run crashes decreased by 50% year-over-year, falling from 4 incidents in January 2024 to 2 in January 2025. Consequently, the hit-and-run rate also declined from 8.3% of all crashes to 4.4%.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
2
Pedestrians Injured
6
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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 year-over-year. The peak day for crashes moved from Monday, with 12 incidents in January 2024, to Friday, with 9 incidents in January 2025. Similarly, the peak hour for crashes shifted from 5 PM in January 2024 to 8 AM in January 2025, with both peak hours recording 7 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The overall injury rate decreased slightly from 18.8% in January 2024 (9 injuries out of 48 crashes) to 17.8% in January 2025 (8 injuries out of 45 crashes). Both periods recorded 0 fatal crashes and 0 fatalities. The proportion of 'No Injury' crashes increased from 72.9% in the prior period to 84.4% in the current period, indicating a higher percentage of crashes with no reported injuries.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor, 'No improper driving,' increased by 21.1% in count, from 19 crashes in January 2024 to 23 crashes in January 2025, and its share rose from 39.6% to 51.1%. Conversely, 'Inattention' crashes decreased by 50% in count, from 6 to 3, and 'Failed to yield right of way' crashes decreased by 33.3% in count, from 3 to 2. Factors like 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner,' 'Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway,' and 'Failure to keep in proper lane or running off road' each increased by 100% in count, from 1 to 2 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring on 'Wet' road surfaces decreased significantly, from 10 in January 2024 to 4 in January 2025, representing a 60% reduction. Similarly, crashes on 'Ice' decreased by 60%, from 5 to 2. Crashes occurring in 'Dark - lighted roadway' conditions decreased by 47.4%, from 19 to 10, while crashes in 'Daylight' conditions increased by 24%, from 25 to 31.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 85 in January 2024 to 92 in January 2025. Among vehicle makes, HONDA-involved crashes increased by 88.9%, from 9 to 17, while TOYOTA-involved crashes remained stable at 10. The 0-15 age group saw an increase in persons involved from 2 to 7, and the 35-44 age group increased from 9 to 18, whereas the 65+ age group decreased from 16 to 12 persons.
Top Vehicle Makes (92 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Vehicle unit records
19 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (86 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 25 mph speed zones increased by 58.3%, from 12 in January 2024 to 19 in January 2025. Conversely, crashes in 30 mph speed zones saw a substantial decrease, from 9 to 1. There were no fatal crashes recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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: 2025-01-01 through 2025-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-01-31 (31 days)
- Geographic scope: GLOUCESTER, MA
- Total crash records analyzed: 45
- Total persons involved: 106
- Total vehicles involved: 92
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: January 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/gloucester/january-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: 2025-01-01 – 2025-01-31
Generated: June 21, 2026 · All rights reserved