ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · QUINCY, MA · JULY 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/quincy/july-2025-report
Monthly Traffic Safety Analysis
164 CRASHES IN
QUINCY, MA
JULY 2025
In July 2025, Quincy, MA experienced 164 crashes, a decrease of 13.7% from the 190 crashes recorded in July 2024. Notably, there were no fatalities in July 2025 compared to one fatality in July 2024, representing a significant positive shift in safety outcomes.
164
▼ -13.7%was 190
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
54
▲ 17.4%was 46
Persons Injured
20
▼ -20.0%was 25
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. 7 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a decrease in total crashes year-over-year, with 164 crashes in July 2025 compared to 190 crashes in July 2024. This represents a reduction of 26 crashes, or approximately 13.7%. However, total injuries increased by 17.4%, from 46 to 54.
20
Hit-and-Run Crashes — July 2025
▼ -20.0% vs prior (25)
The number of hit-and-run crashes decreased from 25 in July 2024 to 20 in July 2025, representing a 20% reduction. The hit-and-run rate also decreased by 1 percentage point, from 13.2% in July 2024 to 12.2% in July 2025, indicating a positive trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
4
Pedestrians Injured
3
Cyclists Injured
47
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Tuesday in both periods, though the count decreased from 44 in July 2024 to 30 in July 2025. The peak hour shifted from 3 PM with 23 crashes in July 2024 to 4 PM with 15 crashes in July 2025, indicating a slight shift in the busiest time for incidents.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
A significant improvement was observed in crash severity, with no fatalities recorded in July 2025 compared to one fatality in July 2024. While serious injuries (code A) increased from 1 to 5, minor injuries (code B) slightly decreased from 25 to 21, and possible injuries (code C) increased from 9 to 16.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, 'Inattention,' saw a substantial decrease of 39 crashes (52%) from 75 in July 2024 to 36 in July 2025. Conversely, 'Failed to yield right of way' increased by 9 crashes (42.9%) from 21 to 30, and 'Followed too closely' increased by 7 crashes (87.5%) from 8 to 15.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Clear weather conditions remained the most common for crashes in both periods, with 140 crashes in July 2025 and 148 in July 2024 occurring in clear or clear/clear conditions. The number of crashes on dry road surfaces decreased from 179 to 151, while crashes on wet surfaces slightly decreased from 10 to 9. Daylight remained the predominant lighting condition for crashes, though the count decreased from 157 to 124.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased by 44, from 370 in July 2024 to 326 in July 2025. Toyota remained the most frequently involved make, though its count decreased from 81 to 58. Honda and Ford saw slight increases in involvement, with Honda going from 41 to 44 and Ford from 34 to 39.
Top Vehicle Makes (326 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Vehicle unit records
58 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (349 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph speed zones decreased from 132 in July 2024 to 97 in July 2025. Conversely, crashes in 55 mph zones increased from 11 to 15 year-over-year. There were no fatal crashes in any speed zone in July 2025, compared to one fatal crash in a 30 mph zone in July 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · 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: 2025-07-01 through 2025-07-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-07-01 through 2025-07-31 (31 days)
- Geographic scope: QUINCY, MA
- Total crash records analyzed: 164
- Total persons involved: 407
- Total vehicles involved: 326
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). "QUINCY, MA Crash Intelligence Report: July 2025." Published June 21, 2026. Reporting period: 2025-07-01 to 2025-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/quincy/july-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: 2025-07-01 – 2025-07-31
Generated: June 21, 2026 · All rights reserved