Monthly Traffic Safety Analysis

86 CRASHES IN
PLYMOUTH, MA
JUNE 2022

All metrics benchmarked againstJune 2021

In June 2022, PLYMOUTH experienced 86 total crashes, an 8.86% increase compared to the 79 crashes reported in June 2021. Notably, total fatalities decreased from 1 in June 2021 to 0 in June 2022, while total injuries rose by 60%, from 20 to 32.

86

8.9%was 79

Total Crash Events

0

-100.0%was 1

Persons Killed

32

60.0%was 20

Persons Injured

2

100.0%was 1

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 · 2022-06-01 to 2022-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in PLYMOUTH saw an upward trend year-over-year, increasing by 7 incidents from 79 crashes in June 2021 to 86 crashes in June 2022. Despite this increase in total crashes, there was a positive trend in safety outcomes with a decrease in fatalities from 1 to 0.

2

Hit-and-Run Crashes — June 2022

100.0% vs prior (1)

Hit-and-run crashes increased from 1 incident in June 2021 to 2 incidents in June 2022. The hit-and-run rate also rose from 1.3% to 2.3% of all crashes year-over-year, indicating an upward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 1-100.0%

2

Pedestrians Injured

Prior: 1100.0%

30

Motorists Injured

Prior: 1866.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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 Saturday, with 18 incidents in June 2022 compared to 15 in June 2021. However, the peak crash hour shifted from 11 PM with 7 crashes in June 2021 to 5 PM with 12 crashes in June 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased from 1 in June 2021 to 0 in June 2022. Serious injuries increased from 1 crash to 2 crashes, and minor injuries rose from 10 crashes to 18 crashes year-over-year. The proportion of crashes resulting in no injury slightly decreased from 74.7% to 70.9% of all crashes.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes2.3%
100.0%prior 1
Minor Injury18minor injury crashes20.9%
80.0%prior 10
Possible Injury5possible injury crashes5.8%
-16.7%prior 6
No Injury61no injury crashes70.9%
3.4%prior 59

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Most severe injury per crash record

Top Contributing Factors

The factor 'Failed to yield right of way' saw a significant increase, rising from 4 crashes in June 2021 to 13 crashes in June 2022, moving from fifth to second most common. 'Operating vehicle in an erratic, reckless, careless, negligent or aggressive manner' also increased from 2 to 7 crashes, entering the top five factors. 'Inattention' decreased slightly from 14 crashes to 13 crashes.

Officer-Reported Primary Contributing Cause

No improper driving19 (22.1%)11.8%prior 17
Failed to yield right of way13 (15.1%)
Inattention13 (15.1%)-7.1%prior 14
Followed too closely7 (8.1%)-12.5%prior 8
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner7 (8.1%)
Other improper action6 (7%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway5 (5.8%)
Over-correcting/over-steering3 (3.5%)
Made an improper turn2 (2.3%)
Operating defective equipment2 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 57 in June 2021 to 69 in June 2022. Crashes on wet road surfaces also increased from 9 to 12 incidents year-over-year. Crashes during daylight hours increased from 60 to 66, while those in dark-lighted roadway conditions decreased from 9 to 7.

Weather

Clear69 (81.2%)
21.1%prior 57
Rain9 (10.6%)
Clear/Unknown2 (2.4%)
Cloudy2 (2.4%)
-81.8%prior 11
Rain/Cloudy1 (1.2%)
Clear/Cloudy1 (1.2%)
Cloudy/Rain1 (1.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Weather condition at time of crash

Lighting

Daylight66 (76.7%)
10.0%prior 60
Dark - lighted roadway7 (8.1%)
-22.2%prior 9
Dark - roadway not lighted7 (8.1%)
0.0%prior 7
Dusk4 (4.7%)
Dark - unknown roadway lighting2 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Lighting condition field

Road Surface

Dry74 (86.0%)
10.4%prior 67
Wet12 (14.0%)
33.3%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 136 to 145 year-over-year. The 16-20 age group saw an increase in representation from 16 to 23 persons, while the 55-64 age group decreased from 32 to 24 persons. NISSAN vehicles showed a notable increase in involvement, rising from 6 to 15 and moving into the second top make ranking.

Top Vehicle Makes (145 vehicles)

1
TOYOTA24 (16.6%)
9.1%prior 22
2
NISSAN15 (10.3%)
150.0%prior 6
3
FORD14 (9.7%)
0.0%prior 14
4
JEEP11 (7.6%)
22.2%prior 9
5
CHEVROLET10 (6.9%)
11.1%prior 9
6
HONDA10 (6.9%)
0.0%prior 10
7
GMC8 (5.5%)
8
SUBARU7 (4.8%)
40.0%prior 5
9
HYUNDAI6 (4.1%)
20.0%prior 5
10
AUDI4 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Vehicle unit records

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

Sex Distribution (150 persons with recorded sex)

Male80 (53.3%)
-10.1%prior 89
Female70 (46.7%)
-1.4%prior 71

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones increased from 25 to 39 incidents, making it the most frequent speed zone for crashes. Conversely, crashes in 35 mph zones decreased from 13 to 6 incidents. There were no fatal crashes in any speed zone in June 2022, compared to 1 fatal crash in a 60 mph zone in June 2021.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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: 2022-06-01 through 2022-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-06-01 through 2022-06-30 (30 days)
  • Geographic scope: PLYMOUTH, MA
  • Total crash records analyzed: 86
  • Total persons involved: 170
  • Total vehicles involved: 145

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). "PLYMOUTH, MA Crash Intelligence Report: June 2022." Published June 21, 2026. Reporting period: 2022-06-01 to 2022-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/plymouth/june-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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