Monthly Traffic Safety Analysis

25 CRASHES IN
AMHERST, MA
SEPTEMBER 2025

All metrics benchmarked againstSeptember 2024

In September 2025, AMHERST, MA experienced a notable decrease in overall crashes, with 25 incidents reported compared to 40 in September 2024, representing a 37.5% reduction. Despite this decrease, total injuries increased by 37.5%, rising from 8 to 11. A significant year-over-year shift was the absence of DUI-related crashes in September 2025, down from 2 in the prior year.

25

-37.5%was 40

Total Crash Events

0

Persons Killed

11

37.5%was 8

Persons Injured

0

Fatal Crash Events

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 · 2025-09-01 to 2025-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in AMHERST, MA showed a downward trend year-over-year, decreasing by 37.5% from 40 crashes in September 2024 to 25 crashes in September 2025. Conversely, the number of total injuries increased by 37.5%, from 8 to 11. There were no fatalities reported in either period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

11

Motorists Injured

Prior: 837.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal pattern of crashes shifted year-over-year. In September 2025, the peak day for crashes was Tuesday with 7 incidents, whereas in September 2024, Thursday saw the highest count with 11 crashes. The peak hour also changed, with 7 p.m. having 3 crashes in September 2025, compared to 4 p.m. with 9 crashes in the prior year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The distribution of crash severity showed some changes year-over-year, though no fatal crashes occurred in either period. Serious injury crashes increased from 0 in September 2024 to 1 in September 2025, while minor injury crashes increased from 4 to 5. Possible injury crashes decreased from 2 to 1 over the same period.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes4%
Minor Injury5minor injury crashes20%
25.0%prior 4
Possible Injury1possible injury crashes4%
-50.0%prior 2
No Injury18no injury crashes72%
-45.5%prior 33

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Most severe injury per crash record

Top Contributing Factors

Several contributing factors saw shifts in their counts year-over-year. 'Inattention' crashes decreased from 11 to 3, and 'Failed to yield right of way' crashes decreased from 6 to 3. Conversely, 'Followed too closely' crashes increased from 2 to 3, and 'Disregarded traffic signs, signals, road markings' appeared as a factor with 2 crashes in September 2025, not being among the top factors in September 2024.

Officer-Reported Primary Contributing Cause

No improper driving5 (20%)-44.4%prior 9
Followed too closely3 (12%)
Failed to yield right of way3 (12%)-50.0%prior 6
Inattention3 (12%)-72.7%prior 11
Over-correcting/over-steering2 (8%)
Fatigued/asleep2 (8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (8%)
Disregarded traffic signs, signals, road markings2 (8%)
Distracted1 (4%)
Glare1 (4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring under 'Clear' weather conditions decreased from 35 to 22 year-over-year, while 'Rain' conditions remained constant with 2 crashes in both periods. For lighting conditions, 'Daylight' crashes decreased from 30 to 16, but crashes in 'Dark - lighted roadway' conditions slightly increased from 5 to 6. The number of crashes on 'Dry' road surfaces decreased from 38 to 23, while 'Wet' road surface crashes remained at 2 in both periods.

Weather

Clear22 (88.0%)
-37.1%prior 35
Rain2 (8.0%)
Cloudy1 (4.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Weather condition at time of crash

Lighting

Daylight16 (64.0%)
-46.7%prior 30
Dark - lighted roadway6 (24.0%)
20.0%prior 5
Dark - roadway not lighted2 (8.0%)
Dusk1 (4.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Lighting condition field

Road Surface

Dry23 (92.0%)
-39.5%prior 38
Wet2 (8.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (44 vehicles)

1
HONDA8 (18.2%)
-11.1%prior 9
2
TOYOTA7 (15.9%)
40.0%prior 5
3
SUBARU6 (13.6%)
-33.3%prior 9
4
CHEVROLET5 (11.4%)
-28.6%prior 7
5
NISSAN4 (9.1%)
6
JEEP2 (4.5%)
7
DODGE2 (4.5%)
8
MERCEDES-BENZ1 (2.3%)
9
VOLKSWAGEN1 (2.3%)
-80.0%prior 5
10
AUDI1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Vehicle unit records

1 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (52 persons with recorded sex)

Female26 (50.0%)
-29.7%prior 37
Male26 (50.0%)
-39.5%prior 43

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 35 mph zones saw the largest decrease, dropping from 13 incidents in September 2024 to 5 in September 2025. Crashes in 25 mph zones, however, increased from 8 to 10 incidents. Overall, crashes decreased across most speed zones, with the proportion of crashes occurring at 25 mph increasing from 20% to 40% of all speed-zoned crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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: 2025-09-01 through 2025-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-09-01 through 2025-09-30 (30 days)
  • Geographic scope: AMHERST, MA
  • Total crash records analyzed: 25
  • Total persons involved: 54
  • Total vehicles involved: 44

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: September 2025." Published June 21, 2026. Reporting period: 2025-09-01 to 2025-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/amherst/september-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

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Amherst, MA Crash Report — September 2025 | ThatCarHitMe.com