Monthly Traffic Safety Analysis

32 CRASHES IN
NORTHAMPTON, MA
NOVEMBER 2025

All metrics benchmarked againstNovember 2024

NORTHAMPTON experienced a decrease in total crashes in November 2025 compared to November 2024, with crashes falling from 42 to 32, representing a 23.8% reduction. The most notable shift was the complete absence of fatalities in November 2025, down from 2 fatalities in the prior year.

32

▼ -23.8%was 42

Total Crash Events

0

▼ -100.0%was 2

Persons Killed

7

▼ -53.3%was 15

Persons Injured

1

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.

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 decline in crash-related incidents year-over-year. Total crashes decreased by 10, from 42 in November 2024 to 32 in November 2025. This reduction was accompanied by a drop in total fatalities from 2 to 0 and a decrease in total injuries from 15 to 7.

1

Hit-and-Run Crashes — November 2025

3.1% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 1↓-100.0%

1

Cyclists Injured

Prior: 2↓-50.0%

6

Motorists Injured

Prior: 13↓-53.8%

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 peak day for crashes shifted from Tuesday in November 2024 (11 crashes) to Friday in November 2025 (8 crashes). The peak hour also changed, moving from 12 PM with 7 crashes in November 2024 to 4 PM with 5 crashes in November 2025. There was a notable decrease in crashes on Tuesdays, falling from 11 to 4, while crashes on Thursdays and Saturdays remained stable with 5 crashes each.

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

Fatal crashes decreased from 2 in November 2024 to 0 in November 2025. The number of serious injury crashes remained constant at 2 in both periods. Minor injury crashes decreased from 5 to 4, and possible injury crashes, which accounted for 2 in the prior period, were absent in the current period.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes6.3%
→0.0%prior 2
Minor Injury4minor injury crashes12.5%
↓-20.0%prior 5
No Injury26no injury crashes81.3%
↓-16.1%prior 31

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', saw a slight decrease from 9 crashes in November 2024 to 8 crashes in November 2025. 'Failed to yield right of way' increased from 5 crashes in November 2024 to 8 crashes in November 2025. 'Inattention' crashes significantly decreased from 10 to 2, while 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' crashes dropped from 4 to 1.

Officer-Reported Primary Contributing Cause

No improper driving8 (25%)↓-11.1%prior 9
Failed to yield right of way8 (25%)↑60.0%prior 5
Inattention2 (6.3%)↓-80.0%prior 10
Followed too closely2 (6.3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (6.3%)
Failure to keep in proper lane or running off road2 (6.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (3.1%)
Made an improper turn1 (3.1%)
Glare1 (3.1%)
Other improper action1 (3.1%)

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 slightly increased from 22 in November 2024 to 23 in November 2025, while 'Cloudy' conditions saw a decrease from 4 to 2 crashes. Crashes on 'Dry' road surfaces decreased from 34 to 28, and 'Wet' road surface crashes decreased from 8 to 3. Crashes occurring in 'Daylight' decreased from 29 to 18, whereas crashes during 'Dawn' increased from 0 to 2.

Weather

Clear23 (71.9%)
↑4.5%prior 22
Clear/Clear3 (9.4%)
Cloudy2 (6.3%)
Cloudy/Rain2 (6.3%)
Rain1 (3.1%)
Rain/Cloudy1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Weather condition at time of crash

Lighting

Daylight18 (56.3%)
↓-37.9%prior 29
Dark - lighted roadway7 (21.9%)
↓-30.0%prior 10
Dusk3 (9.4%)
Dark - roadway not lighted2 (6.3%)
Dawn2 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Lighting condition field

Road Surface

Dry28 (87.5%)
↓-17.6%prior 34
Wet3 (9.4%)
↓-62.5%prior 8
Ice1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Road surface condition field

Vehicles & Demographics

Among top vehicle makes, TOYOTA crashes decreased from 17 in November 2024 to 8 in November 2025, while HONDA crashes increased from 10 to 12. The age group '0-15' experienced a significant decrease in persons involved in crashes, falling from 14 to 1, and the '65+' age group also saw a substantial drop from 25 to 11. Conversely, the '16-20' age group increased from 6 to 10 persons involved in crashes.

Top Vehicle Makes (58 vehicles)

1
HONDA12 (20.7%)
↑20.0%prior 10
2
TOYOTA8 (13.8%)
↓-52.9%prior 17
3
FORD7 (12.1%)
↓-22.2%prior 9
4
SUBARU6 (10.3%)
↓-33.3%prior 9
5
CHEVROLET5 (8.6%)
6
NISSAN5 (8.6%)
7
HYUNDAI2 (3.4%)
8
JEEP2 (3.4%)
9
VOLKSWAGEN1 (1.7%)
10
BUIC1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Vehicle unit records

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

Sex Distribution (68 persons with recorded sex)

Male40 (58.8%)
↓-14.9%prior 47
Female28 (41.2%)
↓-42.9%prior 49

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 the 25 mph speed zone decreased from 13 in November 2024 to 9 in November 2025, and 30 mph zone crashes decreased from 11 to 8. The 35 mph speed zone saw a slight increase in crashes from 8 to 9. Notably, the 65 mph speed zone experienced an increase in crashes from 3 to 5, and fatalities in this zone decreased from 1 to 0.

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: NORTHAMPTON, MA
  • Total crash records analyzed: 32
  • Total persons involved: 72
  • Total vehicles involved: 58

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). "NORTHAMPTON, 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/northampton/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

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Northampton, MA Crash Report — November 2025 | ThatCarHitMe.com