ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SOUTH HADLEY, MA · NOVEMBER 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/south-hadley/november-2025-report
Monthly Traffic Safety Analysis
18 CRASHES IN
SOUTH HADLEY, MA
NOVEMBER 2025
In November 2025, SOUTH HADLEY experienced 18 crashes, a decrease of 30.8% compared to the 26 crashes recorded in November 2024. A notable shift includes the increase in DUI-related crashes from zero in the prior year to 3 in the current period.
18
▼ -30.8%was 26
Total Crash Events
0
Persons Killed
6
▼ -40.0%was 10
Persons Injured
1
▼ -50.0%was 2
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 · 2025-11-01 to 2025-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a significant decrease in crash activity, with total crashes falling by 30.8% from 26 to 18 year-over-year. Concurrently, total injuries also saw a reduction, dropping from 10 to 6 in the current period.
1
Hit-and-Run Crashes — November 2025
▼ -50.0% vs prior (2)
The number of hit-and-run crashes decreased from 2 in November 2024 to 1 in November 2025. The hit-and-run crash rate also saw a decrease, moving from 7.7% in the prior period to 5.6% in the current period, indicating a downward trend.
Vulnerable Road User Casualties
0
Motorists Killed
6
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Temporal patterns show shifts in peak activity; the peak crash day moved from Wednesday with 8 crashes in the prior period to Friday with 4 crashes in the current period. While both periods had a peak hour of 4 crashes, the peak shifted from 5 PM in the prior year to 12 PM in the current year. Crashes on Wednesday decreased significantly from 8 to 0, while Sunday crashes increased from 0 to 3.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Neither period recorded any fatalities or fatal crashes. Total injuries decreased from 10 in November 2024 to 6 in November 2025. The proportion of crashes resulting in serious injury (Severity A) decreased from 7.7% (2 crashes) in the prior period to 5.6% (1 crash) in the current period. Crashes with minor injuries (Severity B) decreased from 4 (15.4%) to 3 (16.7%). The current period also reported 1 crash with a possible injury (Severity C), which was not explicitly listed in the prior period's severity breakdown.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Most severe injury per crash record
Top Contributing Factors
Inattention remained a significant contributing factor, decreasing from 7 crashes in the prior period to 4 crashes in the current period. Crashes attributed to 'No improper driving' also decreased from 6 to 4. Conversely, 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' increased from 0 crashes to 3 crashes, and 'Failed to yield right of way' increased from 1 to 2 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The number of crashes occurring in clear weather conditions decreased from 24 to 14 year-over-year, while crashes in cloudy conditions increased from 1 to 2. Crashes during daylight decreased from 15 to 8, but crashes in 'Dark - lighted roadway' conditions increased from 5 to 8. Regarding road surface, dry condition crashes decreased from 22 to 15, while wet condition crashes increased from 2 to 3.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Road surface condition field
Vehicles & Demographics
Top Vehicle Makes (27 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Vehicle unit records
2 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (32 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 MPH speed zones increased from 6 in the prior period to 10 in the current period, representing the highest concentration of crashes. Conversely, crashes in 35 MPH speed zones saw a significant decrease, falling from 9 to 1. There were no fatal crashes recorded in any speed zone for either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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: 2025-11-01 through 2025-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-11-01 through 2025-11-30 (30 days)
- Geographic scope: SOUTH HADLEY, MA
- Total crash records analyzed: 18
- Total persons involved: 34
- Total vehicles involved: 27
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). "SOUTH HADLEY, MA Crash Intelligence Report: November 2025." Published June 21, 2026. Reporting period: 2025-11-01 to 2025-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/south-hadley/november-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: 2025-11-01 – 2025-11-30
Generated: June 21, 2026 · All rights reserved