Monthly Traffic Safety Analysis

16 CRASHES IN
ADAMS, MA
JANUARY 2026

All metrics benchmarked againstJanuary 2025

In January 2026, ADAMS experienced 16 crashes, a decrease from the 19 crashes recorded in January 2025. This represents a 15.8% reduction in total crashes year-over-year. A notable shift includes the absence of DUI-related crashes in the current period, compared to two such incidents in the prior year.

16

-15.8%was 19

Total Crash Events

0

Persons Killed

0

Persons Injured

2

-33.3%was 3

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. 16 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a decrease in crashes, with total incidents falling from 19 in January 2025 to 16 in January 2026. This represents a 15.8% reduction in the total number of crashes. Fatalities and injuries remained at zero for both periods.

2

Hit-and-Run Crashes — January 2026

-33.3% vs prior (3)

The number of hit-and-run crashes decreased from 3 in January 2025 to 2 in January 2026. Consequently, the hit-and-run rate also saw a decrease, moving from 15.8% in the prior period to 12.5% in the current period, indicating a downward trend.

When Crashes Happen

The peak day for crashes shifted from Friday in January 2025, which saw 5 crashes, to Monday in January 2026, also with 5 crashes. The peak hour remained 2 PM in both periods, with crashes increasing from 3 in the prior year to 4 in the current year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash time field aggregated by hour (0-23)

Top Contributing Factors

The count of crashes attributed to "No improper driving" decreased from 8 in January 2025 to 6 in January 2026. Conversely, crashes due to "Inattention" increased from 2 to 3, while "Followed too closely" incidents decreased from 2 to 1. Factors like "Made an improper turn" and "Other improper action," each with 2 crashes in the prior period, were not among the top contributing factors in the current period.

Officer-Reported Primary Contributing Cause

No improper driving6 (37.5%)-25.0%prior 8
Inattention3 (18.8%)
Visibility obstructed2 (12.5%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (6.3%)
Failed to yield right of way1 (6.3%)
Failure to keep in proper lane or running off road1 (6.3%)
Followed too closely1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather decreased from 10 in January 2025 to 8 in January 2026, while those in 'Snow' conditions increased from 3 to 5. Regarding road surface, crashes on 'Dry' surfaces significantly decreased from 14 to 4, whereas crashes on 'Snow' surfaces increased from 2 to 6, and 'Wet' surfaces increased from 2 to 4. Crashes during 'Daylight' decreased from 11 to 8, while those in 'Dark - lighted roadway' increased from 4 to 5.

Weather

Clear8 (50.0%)
-20.0%prior 10
Snow5 (31.3%)
Clear/Cloudy1 (6.3%)
Clear/Snow1 (6.3%)
Cloudy1 (6.3%)
-83.3%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Weather condition at time of crash

Lighting

Daylight8 (50.0%)
-27.3%prior 11
Dark - lighted roadway5 (31.3%)
Dusk2 (12.5%)
Dark - roadway not lighted1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Lighting condition field

Road Surface

Snow6 (37.5%)
Dry4 (25.0%)
-71.4%prior 14
Wet4 (25.0%)
Ice1 (6.3%)
Slush1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (28 vehicles)

1
CHEVROLET5 (17.9%)
2
FORD5 (17.9%)
3
DODGE3 (10.7%)
4
TOYOTA3 (10.7%)
5
JEEP3 (10.7%)
6
HONDA2 (7.1%)
-60.0%prior 5
7
GMC1 (3.6%)
8
CADI1 (3.6%)
9
CHRYSLER1 (3.6%)
10
BMW1 (3.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Vehicle unit records

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

Sex Distribution (26 persons with recorded sex)

Male19 (73.1%)
35.7%prior 14
Female7 (26.9%)
-22.2%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 10 mph zones decreased from 4 in January 2025 to 1 in January 2026, and 25 mph zones saw a decrease from 6 to 3 crashes. Conversely, crashes in 35 mph zones increased from 2 to 5. Crashes in 30 mph and 45 mph zones remained stable at 3 and 2 respectively, across both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · 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: 2026-01-01 through 2026-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2026-01-01 through 2026-01-31 (31 days)
  • Geographic scope: ADAMS, MA
  • Total crash records analyzed: 16
  • Total persons involved: 32
  • Total vehicles involved: 28

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). "ADAMS, MA Crash Intelligence Report: January 2026." Published June 21, 2026. Reporting period: 2026-01-01 to 2026-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/adams/january-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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Adams, MA Crash Report — January 2026 | ThatCarHitMe.com