ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GLOUCESTER, MA · MAY 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/may-2025-report
Monthly Traffic Safety Analysis
44 CRASHES IN
GLOUCESTER, MA
MAY 2025
In May 2025, Gloucester recorded 44 total crashes, a 20% decrease compared to the 55 crashes reported in May 2024. The total number of injuries also saw a reduction, from 11 to 9. The most significant year-over-year shift was a 75% reduction in hit-and-run crashes, dropping from 8 to 2.
44
▼ -20.0%was 55
Total Crash Events
0
Persons Killed
9
▼ -18.2%was 11
Persons Injured
2
▼ -75.0%was 8
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 · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a decrease in crash activity year-over-year for May. Total crashes declined by 20%, from 55 in May 2024 to 44 in May 2025. Similarly, total injuries decreased by 18.2%, from 11 to 9 over the same period.
2
Hit-and-Run Crashes — May 2025
▼ -75.0% vs prior (8)
Hit-and-run crashes experienced a substantial decrease, falling from 8 incidents in May 2024 to 2 incidents in May 2025. This represents a 75% reduction in the count of hit-and-run crashes. The hit-and-run rate also decreased significantly, from 14.5% of all crashes in May 2024 to 4.5% in May 2025, indicating a downward trend.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
8
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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 between the two periods. The peak day for crashes moved from Monday, with 12 incidents in May 2024, to Thursday, with 10 incidents in May 2025. The peak crash hour also shifted from 1 PM (9 crashes) in May 2024 to 2 PM (8 crashes) in May 2025.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatalities reported in either May 2024 or May 2025. The number of serious injury crashes decreased from 1 in May 2024 to 0 in May 2025. Minor injury crashes remained constant at 4, but their proportion of total crashes increased from 7.3% to 9.1%, while possible injury crashes remained at 3, with their proportion increasing from 5.5% to 6.8%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record
Top Contributing Factors
The count of crashes attributed to 'No improper driving' decreased from 26 in May 2024 to 22 in May 2025. Crashes involving 'Failed to yield right of way' increased from 2 to 4, while 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased from 3 to 2. 'Followed too closely' crashes increased from 1 to 2, and 'Fatigued/asleep' emerged as a factor with 2 crashes in May 2025, not being listed among the top factors in May 2024.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring under 'Clear' weather conditions decreased from 27 in May 2024 to 22 in May 2025, while 'Rain' condition crashes slightly increased from 3 to 4. For lighting, 'Daylight' crashes decreased from 46 to 38, and 'Dark - lighted roadway' crashes decreased from 6 to 4. Similarly, crashes on 'Dry' road surfaces decreased from 47 to 37, and 'Wet' road surface crashes decreased from 8 to 6.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes decreased from 113 to 93 year-over-year. In terms of vehicle makes, TOYOTA rose from 10 crashes to 14, becoming the most frequent make, while CHEVROLET dropped from 12 crashes to 7. Regarding age distribution, the 35-44 age group saw an increase in representation from 8 to 14 persons, and the 65+ age group increased from 19 to 24 persons, while the 21-25 age group decreased from 14 to 8 persons.
Top Vehicle Makes (82 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records
12 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (80 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 25 mph speed zones slightly decreased from 19 in May 2024 to 18 in May 2025. Crashes in 55 mph zones saw a more significant reduction, from 5 to 2. Conversely, crashes in 35 mph zones increased from 2 to 4, and 30 mph zones recorded 3 crashes in May 2025, not appearing in May 2024 data.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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: 2025-05-01 through 2025-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-05-01 through 2025-05-31 (31 days)
- Geographic scope: GLOUCESTER, MA
- Total crash records analyzed: 44
- Total persons involved: 93
- 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: May 2025." Published June 21, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/gloucester/may-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: 2025-05-01 – 2025-05-31
Generated: June 21, 2026 · All rights reserved