ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · AMHERST, 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/amherst/november-2025-report
Monthly Traffic Safety Analysis
32 CRASHES IN
AMHERST, MA
NOVEMBER 2025
In November 2025, Amherst experienced 32 total crashes, a decrease from 36 crashes in November 2024, representing an 11.1% reduction. Total injuries also saw a notable decline, falling from 7 to 5, a 28.6% decrease. This period marked a shift in crash patterns, including changes in peak crash days and a decrease in serious injuries.
32
▼ -11.1%was 36
Total Crash Events
0
Persons Killed
5
▼ -28.6%was 7
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
Overall crash data for Amherst indicates a downward trend year-over-year. Total crashes decreased by 11.1%, from 36 in November 2024 to 32 in November 2025. Similarly, total injuries decreased by 28.6%, from 7 to 5, suggesting an improvement in safety outcomes for the period.
1
Hit-and-Run Crashes — November 2025
▼ -50.0% vs prior (2)
Hit-and-run crashes decreased by 50% year-over-year, from 2 crashes in November 2024 to 1 crash in November 2025. This resulted in a reduction of the hit-and-run rate from 5.6% to 3.1% of all crashes.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
4
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
The temporal distribution of crashes shifted significantly year-over-year. In November 2024, Friday was the peak day with 15 crashes, while in November 2025, crashes were more evenly distributed, with Sunday, Monday, and Saturday each recording 6 crashes. The peak crash hour also shifted from 5 PM (5 crashes) in the prior period to 3 PM (6 crashes) in the current period.
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
There were no fatalities in either November 2024 or November 2025. Total injuries decreased from 7 to 5. Serious injuries (Severity A) decreased from 2 to 1, while minor injuries (Severity B) decreased from 3 to 2. Conversely, possible injuries (Severity C) increased from 1 to 2, and crashes with no injuries decreased from 30 to 26.
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
The top contributing factor, 'No improper driving,' increased from 11 crashes in November 2024 to 15 crashes in November 2025, and its share of all crashes rose from 30.6% to 46.9%. 'Inattention' related crashes decreased by 2, from 4 to 2, while 'Disregarded traffic signs, signals, road markings' decreased from 2 crashes to 1. Factors like 'Failed to yield right of way,' 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner,' and 'Followed too closely' maintained consistent counts of 5, 3, and 3 crashes, respectively, across both periods.
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
Crashes occurring in 'Clear' weather conditions decreased from 26 in November 2024 to 18 in November 2025, while crashes in 'Rain' increased from 5 to 7. Under 'Daylight' conditions, crashes decreased from 18 to 8, but crashes during 'Dusk' increased from 1 to 6. Crashes on 'Dry' road surfaces decreased from 29 to 23, while 'Wet' surface crashes slightly increased from 7 to 8, and 1 crash occurred on 'Snow' in the current period.
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
The total number of vehicles involved in crashes decreased from 64 in November 2024 to 54 in November 2025. Toyota became the most frequently involved make with 13 vehicles, up from 11, while Honda involvement decreased from 11 to 2. The 16-20 age group saw a decrease in persons involved, from 23 to 12, whereas the 21-25 age group increased from 13 to 18. Both male and female involvement in crashes decreased, from 36 to 34 for males and 38 to 27 for females.
Top Vehicle Makes (54 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 (61 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 25 mph zones decreased from 12 in November 2024 to 9 in November 2025, and crashes in 40 mph zones decreased from 8 to 3. Conversely, crashes in 35 mph zones increased from 6 to 9. No fatal crashes were recorded in any speed limit zone during 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: AMHERST, MA
- Total crash records analyzed: 32
- Total persons involved: 63
- Total vehicles involved: 54
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). "AMHERST, 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/amherst/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