Monthly Traffic Safety Analysis

15 CRASHES IN
MARION, MA
JANUARY 2023

All metrics benchmarked againstJanuary 2022

Total crashes in MARION decreased by 6.25%, from 16 in January 2022 to 15 in January 2023. Despite this reduction, the number of persons sustaining serious injuries doubled, rising from 1 in January 2022 to 2 in January 2023.

15

-6.3%was 16

Total Crash Events

0

Persons Killed

5

25.0%was 4

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 · 2023-01-01 to 2023-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in MARION decreased by 6.25%, from 16 in January 2022 to 15 in January 2023. Despite this decrease in total crashes, the total number of injured persons rose by 25%, from 4 in January 2022 to 5 in January 2023. Fatalities remained stable at 0 in both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

5

Motorists Injured

Prior: 425.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Sunday in January 2022 (5 crashes) to Monday and Tuesday in January 2023 (4 crashes each). The peak hour also changed, moving from 11 PM in January 2022 (2 crashes) to 11 AM in January 2023 (3 crashes). Crashes on Saturdays decreased from 3 in January 2022 to 0 in January 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both January 2022 and January 2023. The total number of injured persons increased by 25%, from 4 in January 2022 to 5 in January 2023. Specifically, persons with serious injuries (Severity A) doubled from 1 in January 2022 to 2 in January 2023, a 100% increase. Persons with minor injuries (Severity B) increased by 50% from 2 to 3, while persons with possible injuries (Severity C) decreased from 1 to 0.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes13.3%
100.0%prior 1
No Injury13no injury crashes86.7%
18.2%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "No improper driving" decreased by 25% in count, from 8 in January 2022 to 6 in January 2023. Conversely, "Failed to yield right of way" crashes increased by 200% in count, rising from 1 in the prior period to 3 in the current period. Factors such as "Exceeded authorized speed limit," "Fatigued/asleep," "Followed too closely," "Glare," and "Physical impairment" were present in January 2022 (1 crash each) but not in January 2023. New factors appearing in January 2023 include "Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway" (1 crash) and "Visibility obstructed" (1 crash).

Officer-Reported Primary Contributing Cause

No improper driving6 (40%)-25.0%prior 8
Failed to yield right of way3 (20%)
Inattention1 (6.7%)
Driving too fast for conditions1 (6.7%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (6.7%)
Visibility obstructed1 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in "Clear" weather conditions decreased from 9 in January 2022 to 6 in January 2023. Crashes in "Dark - roadway not lighted" conditions saw a decrease of 4 crashes, from 6 in January 2022 to 2 in January 2023. Conversely, crashes during "Daylight" conditions increased from 8 to 9. The number of crashes on "Dry" road surfaces increased from 9 to 10, while "Wet" and "Snow" road surface crashes remained stable at 3 and 2, respectively.

Weather

Clear6 (40.0%)
-33.3%prior 9
Clear/Cloudy2 (13.3%)
Snow/Cloudy2 (13.3%)
Cloudy1 (6.7%)
Cloudy/Rain1 (6.7%)
Rain1 (6.7%)
Snow1 (6.7%)
Clear/Fog, smog, smoke1 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Weather condition at time of crash

Lighting

Daylight9 (60.0%)
12.5%prior 8
Dark - roadway not lighted2 (13.3%)
-66.7%prior 6
Dark - lighted roadway1 (6.7%)
Dark - unknown roadway lighting1 (6.7%)
Dawn1 (6.7%)
Dusk1 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Lighting condition field

Road Surface

Dry10 (66.7%)
11.1%prior 9
Wet3 (20.0%)
Snow2 (13.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (23 vehicles)

1
FORD5 (21.7%)
2
NISSAN4 (17.4%)
3
TOYOTA4 (17.4%)
4
HONDA3 (13%)
5
JEEP1 (4.3%)
6
MERCEDES-BENZ1 (4.3%)
7
BMW1 (4.3%)
8
CAT1 (4.3%)
9
CHEVROLET1 (4.3%)
10
GMC1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Vehicle unit records

Sex Distribution (25 persons with recorded sex)

Female13 (52.0%)
0.0%prior 13
Male11 (44.0%)
-15.4%prior 13
X / Unspecified1 (4.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 MPH speed zone increased by 200%, from 1 in January 2022 to 3 in January 2023. The 40 MPH speed zone also saw an increase of 50%, with crashes rising from 2 to 3. Conversely, crashes in the 50 MPH speed zone decreased by 50%, from 6 to 3, and crashes in the 65 MPH speed zone decreased by 80%, from 5 to 1. Additionally, January 2023 recorded crashes in 5 MPH (1 crash) and 15 MPH (2 crashes) zones, which had no recorded crashes in January 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · 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: 2023-01-01 through 2023-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-01-31 (31 days)
  • Geographic scope: MARION, MA
  • Total crash records analyzed: 15
  • Total persons involved: 25
  • Total vehicles involved: 23

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 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/marion/january-2023-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 2023 | ThatCarHitMe.com