Monthly Traffic Safety Analysis

42 CRASHES IN
NORTH ADAMS, MA
FEBRUARY 2026

All metrics benchmarked againstFebruary 2025

NORTH ADAMS experienced a significant increase in total crashes, rising by 50% from 28 in February 2025 to 42 in February 2026. This period also saw a notable increase in crashes occurring at stop signs, which jumped from 1 to 8 year-over-year. Total injuries also increased by 50%, from 2 to 3.

42

50.0%was 28

Total Crash Events

0

Persons Killed

3

50.0%was 2

Persons Injured

4

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 · 2026-02-01 to 2026-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in NORTH ADAMS trended upwards year-over-year, with total crashes increasing by 50% from 28 in February 2025 to 42 in February 2026. This rise was accompanied by a 50% increase in total injuries, from 2 to 3, while fatalities remained at 0 in both periods.

4

Hit-and-Run Crashes — February 2026

0.0% vs prior (4)

The number of hit-and-run crashes remained stable at 4 for both February 2025 and February 2026. However, the hit-and-run crash rate decreased from 14.3% in the prior period to 9.5% in the current period, reflecting a lower proportion of total crashes being hit-and-run incidents.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 0%

2

Motorists Injured

Prior: 20.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · 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 with 8 crashes in the prior period to Sunday, Tuesday, and Wednesday, all tied with 7 crashes, in the current period. The peak hour also changed, moving from 5 PM with 4 crashes in the prior period to 12 PM and 3 PM, both recording 5 crashes, in the current period. Crashes in the current period showed an increase across most days of the week and during both morning and afternoon hours compared to the prior period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 for both February 2025 and February 2026. Total injuries increased from 2 in the prior period to 3 in the current period. The proportion of crashes resulting in injury (either Minor or Possible) remained consistent at 7.1% for both periods.

Outcome by Severity (Crash Events)

Possible Injury3possible injury crashes7.1%
No Injury39no injury crashes92.9%
50.0%prior 26

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, "No improper driving," decreased by 1 crash from 14 in the prior period to 13 in the current period, with its share of total crashes dropping from 50% to 31%. "Failed to yield right of way" crashes increased by 3, rising from 1 crash to 4 crashes, while "Inattention" crashes also increased by 2, from 1 crash to 3 crashes. "Followed too closely" emerged as a factor with 3 crashes in the current period, not being a top factor in the prior period.

Officer-Reported Primary Contributing Cause

No improper driving13 (31%)-7.1%prior 14
Failed to yield right of way4 (9.5%)
Failure to keep in proper lane or running off road3 (7.1%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway3 (7.1%)
Followed too closely3 (7.1%)
Inattention3 (7.1%)
Other improper action2 (4.8%)
Visibility obstructed2 (4.8%)
Driving too fast for conditions2 (4.8%)
Fatigued/asleep1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in "Snow" weather conditions increased from 5 in the prior period to 8 in the current period. Similarly, crashes on "Snow" road surfaces saw a substantial increase from 5 to 15 year-over-year. The number of crashes occurring in "Daylight" conditions also rose significantly from 18 to 29.

Weather

Clear17 (40.5%)
0.0%prior 17
Snow8 (19.0%)
Cloudy6 (14.3%)
Clear/Cloudy5 (11.9%)
Clear/Other2 (4.8%)
Clear/Severe crosswinds1 (2.4%)
Cloudy/Snow1 (2.4%)
Snow/Blowing sand, snow1 (2.4%)
Snow/Cloudy1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Weather condition at time of crash

Lighting

Daylight29 (69.0%)
61.1%prior 18
Dark - lighted roadway7 (16.7%)
16.7%prior 6
Dusk3 (7.1%)
Dark - roadway not lighted2 (4.8%)
Other1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Lighting condition field

Road Surface

Dry18 (42.9%)
38.5%prior 13
Snow15 (35.7%)
200.0%prior 5
Ice4 (9.5%)
-20.0%prior 5
Wet4 (9.5%)
Slush1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (73 vehicles)

1
TOYOTA13 (17.8%)
2
CHEVROLET9 (12.3%)
50.0%prior 6
3
HONDA9 (12.3%)
50.0%prior 6
4
FORD8 (11%)
5
SUBARU7 (9.6%)
40.0%prior 5
6
HYUNDAI5 (6.8%)
7
JEEP4 (5.5%)
8
NISSAN4 (5.5%)
9
GMC3 (4.1%)
10
VOLVO1 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Vehicle unit records

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

Sex Distribution (72 persons with recorded sex)

Male44 (61.1%)
109.5%prior 21
Female28 (38.9%)
40.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone increased from 9 in the prior period to 13 in the current period, making it the zone with the most crashes in both periods. Crashes in the 35 mph zone also saw a notable increase, rising from 3 to 8. No fatal crashes were recorded in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · 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: 2026-02-01 through 2026-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2026-02-01 through 2026-02-28 (28 days)
  • Geographic scope: NORTH ADAMS, MA
  • Total crash records analyzed: 42
  • Total persons involved: 87
  • Total vehicles involved: 73

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). "NORTH ADAMS, MA Crash Intelligence Report: February 2026." Published June 21, 2026. Reporting period: 2026-02-01 to 2026-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/north-adams/february-2026-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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North Adams, MA Crash Report — February 2026 | ThatCarHitMe.com