Monthly Traffic Safety Analysis

31 CRASHES IN
MARSHFIELD, MA
MARCH 2022

All metrics benchmarked againstMarch 2021

Total crashes in Marshfield for March 2022 increased to 31, representing a 29.17% rise from the 24 crashes recorded in March 2021. This period also saw a significant increase in severity, with total fatalities rising from 0 to 1 and total injuries more than doubling from 7 to 15.

31

29.2%was 24

Total Crash Events

1

Persons Killed

15

114.3%was 7

Persons Injured

1

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 2 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash activity in March 2022 showed an upward trend compared to March 2021. Total crashes increased by 29.17%, from 24 to 31. This was accompanied by a substantial increase in severity, with total fatalities rising from 0 to 1 and total injuries increasing by 114.29% to 15.

1

Hit-and-Run Crashes — March 2022

3.2% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

1

Pedestrians Injured

Prior: 0%

14

Motorists Injured

Prior: 7100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year, with the peak crash day moving from Monday (6 crashes) in March 2021 to Thursday (7 crashes) in March 2022. The peak crash hour also changed, occurring at 6 p.m. (4 crashes) in the prior period and at 2 p.m. (5 crashes) in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased significantly, with total fatalities rising from 0 in March 2021 to 1 in March 2022, resulting in a fatal rate of 3.23% in the current period. Total injuries increased by 114.29%, from 7 in the prior period to 15 in the current period. Additionally, serious injury crashes, which were 0 in the prior period, accounted for 1 crash (3.2%) in March 2022.

Outcome by Severity (Crash Events)

Fatal1fatal crashes3.2%
Serious Injury1serious injury crashes3.2%
Minor Injury4minor injury crashes12.9%
33.3%prior 3
Possible Injury4possible injury crashes12.9%
100.0%prior 2
No Injury19no injury crashes61.3%
5.6%prior 18

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'No improper driving' remained the most frequent, increasing from 9 crashes in March 2021 to 12 crashes in March 2022, a 33.3% increase in count. 'Inattention' saw a substantial 200% increase in count, rising from 2 crashes in the prior period to 6 crashes in the current period. Conversely, 'Failed to yield right of way' decreased by 66.7% in count, from 3 crashes to 1 crash.

Officer-Reported Primary Contributing Cause

No improper driving12 (38.7%)33.3%prior 9
Inattention6 (19.4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (9.7%)
Fatigued/asleep1 (3.2%)
Distracted1 (3.2%)
Over-correcting/over-steering1 (3.2%)
Glare1 (3.2%)
Emotional1 (3.2%)
Failed to yield right of way1 (3.2%)
Failure to keep in proper lane or running off road1 (3.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

While 'Clear' weather remained the most common condition (17 crashes in both periods), there was a notable shift towards adverse road conditions. Crashes on 'Wet' road surfaces increased from 1 in March 2021 to 7 in March 2022. Additionally, 'Ice' and 'Snow' conditions, which were not present in the prior period, contributed to 2 and 1 crash respectively in the current period.

Weather

Clear17 (56.7%)
0.0%prior 17
Cloudy4 (13.3%)
Cloudy/Rain3 (10.0%)
Rain2 (6.7%)
Clear/Other1 (3.3%)
Rain/Snow1 (3.3%)
Sleet, hail (freezing rain or drizzle)/Blowing sand, snow1 (3.3%)
Snow/Sleet, hail (freezing rain or drizzle)1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Weather condition at time of crash

Lighting

Daylight18 (60.0%)
-5.3%prior 19
Dark - lighted roadway8 (26.7%)
60.0%prior 5
Dark - unknown roadway lighting1 (3.3%)
Dusk1 (3.3%)
Dawn1 (3.3%)
Dark - roadway not lighted1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Lighting condition field

Road Surface

Dry19 (65.5%)
-17.4%prior 23
Wet7 (24.1%)
Ice2 (6.9%)
Snow1 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (47 vehicles)

1
FORD6 (12.8%)
-40.0%prior 10
2
TOYOTA5 (10.6%)
-54.5%prior 11
3
HONDA5 (10.6%)
4
CHEVROLET5 (10.6%)
5
JEEP4 (8.5%)
6
NISSAN3 (6.4%)
7
SUBARU2 (4.3%)
8
MERCEDES-BENZ2 (4.3%)
9
HYUNDAI2 (4.3%)
10
AUDI1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Vehicle unit records

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

Sex Distribution (56 persons with recorded sex)

Male38 (67.9%)
31.0%prior 29
Female18 (32.1%)
-41.9%prior 31

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes at the 30 mph speed limit experienced the largest increase, rising from 4 crashes in March 2021 to 9 crashes in March 2022, and this zone recorded the only fatal crash in the current period. In contrast, crashes at the 45 mph speed limit significantly decreased from 6 crashes to 1 crash. The 25 mph zone also saw an increase in crashes, from 5 to 7.

Fatal crashes by zone: 30 mph: 1 of 9 (11.111%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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: 2022-03-01 through 2022-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-03-01 through 2022-03-31 (31 days)
  • Geographic scope: MARSHFIELD, MA
  • Total crash records analyzed: 31
  • Total persons involved: 61
  • Total vehicles involved: 47

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). "MARSHFIELD, MA Crash Intelligence Report: March 2022." Published June 21, 2026. Reporting period: 2022-03-01 to 2022-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/marshfield/march-2022-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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Marshfield, MA Crash Report — March 2022 | ThatCarHitMe.com