Monthly Traffic Safety Analysis

5 CRASHES IN
MARION, MA
JANUARY 2026

All metrics benchmarked againstJanuary 2025

In January 2026, MARION experienced 5 crashes, a 150% increase compared to the 2 crashes reported in January 2025. A notable shift was the appearance of speeding-related crashes, which rose from 0 in January 2025 to 3 in January 2026.

5

150.0%was 2

Total Crash Events

0

Persons Killed

1

-66.7%was 3

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 · 2026-01-01 to 2026-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in MARION saw a significant upward trend, increasing by 150% from 2 crashes in January 2025 to 5 crashes in January 2026. This represents an increase of 3 crashes year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

1

Motorists Injured

Prior: 3-66.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Thursday in both periods, with 2 crashes in January 2026 compared to 1 crash in January 2025. The peak crash hour shifted from 3 p.m. in January 2025 to 8 p.m. in January 2026.

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)

Crash Severity Breakdown

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes20%
No Injury4no injury crashes80%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Most severe injury per crash record

Top Contributing Factors

In January 2026, 'Driving too fast for conditions' was a factor in 2 crashes, and 'Exceeded authorized speed limit' was a factor in 1 crash; neither of these factors were recorded in January 2025. Conversely, 'No improper driving' and 'Physical impairment' were each factors in 1 crash in January 2025 but were not recorded as factors in January 2026.

Officer-Reported Primary Contributing Cause

Driving too fast for conditions2 (40%)
Exceeded authorized speed limit1 (20%)
Inattention1 (20%)
Operating defective equipment1 (20%)

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

In January 2026, 3 crashes occurred in Clear/Clear weather, 1 in Cloudy, and 1 in Rain, while January 2025 reported 1 crash in Clear and 1 in Clear/Clear conditions. Lighting conditions in January 2026 included 2 crashes in Daylight, 2 at Dusk, and 1 in Dark - lighted roadway, compared to January 2025 with 1 crash in Dark - roadway not lighted and 1 in Daylight. Road surface data was not available for January 2025, but January 2026 recorded 3 crashes on Dry roads, 1 on Snow, and 1 on Wet roads.

Weather

Clear/Clear3 (60.0%)
Cloudy1 (20.0%)
Rain1 (20.0%)

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

Lighting

Daylight2 (40.0%)
Dusk2 (40.0%)
Dark - lighted roadway1 (20.0%)

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

Road Surface

Dry3 (60.0%)
Snow1 (20.0%)
Wet1 (20.0%)

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 (7 vehicles)

1
MAZDA2 (28.6%)
2
NISSAN2 (28.6%)
3
FORD1 (14.3%)
4
SUBARU1 (14.3%)
5
TOYOTA1 (14.3%)

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

Sex Distribution (8 persons with recorded sex)

Male6 (75.0%)
200.0%prior 2
Female2 (25.0%)
100.0%prior 1

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 65 mph zones increased from 1 in January 2025 to 3 in January 2026. Additionally, 1 crash occurred in a 25 mph zone and 1 in a 35 mph zone in January 2026, neither of which had crashes reported in January 2025. No fatal crashes were reported in any speed zone during either period.

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: MARION, MA
  • Total crash records analyzed: 5
  • Total persons involved: 8
  • Total vehicles involved: 7

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). "MARION, 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/marion/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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Marion, MA Crash Report — January 2026 | ThatCarHitMe.com