Monthly Traffic Safety Analysis

57 CRASHES IN
PLYMOUTH, MA
MARCH 2023

All metrics benchmarked againstMarch 2022

In March 2023, Plymouth experienced 57 crashes, an increase from 53 crashes in March 2022, representing a 7.55% rise. A notable shift was observed in speeding-related crashes, which doubled from 2 in March 2022 to 4 in March 2023.

57

7.5%was 53

Total Crash Events

0

Persons Killed

27

-12.9%was 31

Persons Injured

1

-66.7%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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates an increase in total crashes year-over-year, rising from 53 crashes in March 2022 to 57 crashes in March 2023. This represents a 7.55% increase in crash incidents during the selected month.

1

Hit-and-Run Crashes — March 2023

-66.7% vs prior (3)

Hit-and-run crashes decreased significantly year-over-year, falling from 3 crashes in March 2022 to 1 crash in March 2023. This resulted in the hit-and-run rate declining from 5.7% to 1.8% of total crashes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

27

Motorists Injured

Prior: 31-12.9%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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 Friday with 13 crashes in March 2022 to Thursday with 13 crashes in March 2023. The peak hour also changed, moving from 2 p.m. with 7 crashes in the prior period to 6 p.m. with 8 crashes in the current period. Additionally, crashes on Monday significantly increased from 3 to 10 year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Despite an increase in total crashes, the total number of injuries decreased from 31 in March 2022 to 27 in March 2023. While no serious injuries were reported in March 2022, there were 2 serious injuries (severity A) in March 2023, accounting for 3.5% of crashes. Minor injuries (severity B) remained at 11 in both periods, though their share decreased from 20.8% to 19.3% of total crashes.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes3.5%
Minor Injury11minor injury crashes19.3%
0.0%prior 11
Possible Injury7possible injury crashes12.3%
-22.2%prior 9
No Injury36no injury crashes63.2%
9.1%prior 33

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Most severe injury per crash record

Top Contributing Factors

The most significant change in contributing factors was 'Failed to yield right of way,' which increased from 5 crashes in March 2022 to 16 crashes in March 2023, representing an increase of 11 crashes. Conversely, 'No improper driving' decreased from 8 crashes to 2 crashes, a reduction of 6 crashes. 'Followed too closely' and 'Inattention' remained constant at 9 and 8 crashes, respectively, in both periods.

Officer-Reported Primary Contributing Cause

Failed to yield right of way16 (28.1%)220.0%prior 5
Followed too closely9 (15.8%)0.0%prior 9
Inattention8 (14%)0.0%prior 8
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (7%)-20.0%prior 5
Driving too fast for conditions3 (5.3%)
Failure to keep in proper lane or running off road2 (3.5%)
No improper driving2 (3.5%)-75.0%prior 8
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (3.5%)
Disregarded traffic signs, signals, road markings2 (3.5%)
Over-correcting/over-steering1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring under 'Clear' weather conditions increased from 39 in March 2022 to 46 in March 2023. Similarly, crashes on 'Dry' road surfaces rose from 39 to 46 year-over-year. The number of crashes during 'Daylight' conditions also saw an increase, from 37 to 43.

Weather

Clear46 (82.1%)
17.9%prior 39
Rain3 (5.4%)
Cloudy/Rain3 (5.4%)
Cloudy2 (3.6%)
Rain/Snow1 (1.8%)
Snow/Sleet, hail (freezing rain or drizzle)1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Weather condition at time of crash

Lighting

Daylight43 (75.4%)
16.2%prior 37
Dark - lighted roadway8 (14.0%)
-11.1%prior 9
Dark - roadway not lighted4 (7.0%)
-20.0%prior 5
Dawn1 (1.8%)
Dusk1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Lighting condition field

Road Surface

Dry46 (80.7%)
17.9%prior 39
Wet10 (17.5%)
0.0%prior 10
Snow1 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 94 in March 2022 to 109 in March 2023. Toyota remained the top vehicle make involved, increasing from 13 to 21 vehicles, while Ford increased from 11 to 16. The age group 35-44 saw the largest increase in persons involved, rising from 15 to 23 year-over-year, and persons aged 0-15 also increased from 4 to 11.

Top Vehicle Makes (109 vehicles)

1
TOYOTA21 (19.3%)
61.5%prior 13
2
FORD16 (14.7%)
45.5%prior 11
3
CHEVROLET13 (11.9%)
62.5%prior 8
4
NISSAN11 (10.1%)
22.2%prior 9
5
HONDA10 (9.2%)
0.0%prior 10
6
SUBARU5 (4.6%)
7
JEEP5 (4.6%)
-37.5%prior 8
8
VOLKSWAGEN3 (2.8%)
9
HYUNDAI3 (2.8%)
10
GMC3 (2.8%)
-40.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Vehicle unit records

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

Sex Distribution (135 persons with recorded sex)

Female68 (50.4%)
15.3%prior 59
Male67 (49.6%)
24.1%prior 54

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 30 mph zones increased from 18 in March 2022 to 21 in March 2023. There was a notable decrease in crashes in 60 mph zones, falling from 10 to 3 year-over-year. Crashes in 40 mph zones increased from 9 to 13, and in 25 mph zones, they rose from 2 to 5.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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: 2023-03-01 through 2023-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-03-01 through 2023-03-31 (31 days)
  • Geographic scope: PLYMOUTH, MA
  • Total crash records analyzed: 57
  • Total persons involved: 140
  • Total vehicles involved: 109

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: March 2023." Published June 21, 2026. Reporting period: 2023-03-01 to 2023-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/plymouth/march-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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Plymouth, MA Crash Report — March 2023 | ThatCarHitMe.com