Monthly Traffic Safety Analysis

74 CRASHES IN
PLYMOUTH, MA
MAY 2025

All metrics benchmarked againstMay 2024

In May 2025, Plymouth experienced 74 total crashes, a decrease from the 105 crashes recorded in May 2024. This represents a significant 29.5% reduction in overall crash incidents year-over-year. The most notable shift is the absence of crash fatalities in May 2025, compared to one fatality in May 2024.

74

▼ -29.5%was 105

Total Crash Events

0

▼ -100.0%was 1

Persons Killed

32

▼ -27.3%was 44

Persons Injured

3

▼ -40.0%was 5

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 · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash incidents in Plymouth are trending downwards, with total crashes decreasing by 31, from 105 in May 2024 to 74 in May 2025. This constitutes a 29.5% reduction in crashes year-over-year. Fatalities also saw a positive trend, decreasing from one in May 2024 to zero in May 2025.

3

Hit-and-Run Crashes — May 2025

▼ -40.0% vs prior (5)

The number of hit-and-run crashes decreased from 5 in May 2024 to 3 in May 2025. The hit-and-run rate also decreased from 4.8% of all crashes in May 2024 to 4.1% in May 2025, indicating a downward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 1↓-100.0%

0

Other Killed

Prior: 0→0.0%

1

Pedestrians Injured

Prior: 0→%

2

Cyclists Injured

Prior: 1↑100.0%

26

Motorists Injured

Prior: 43↓-39.5%

3

Other Injured

Prior: 0→%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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 in May 2024 (22 crashes) to Saturday in May 2025 (19 crashes). Similarly, the peak hour changed from 2 PM in May 2024 (12 crashes) to 3 PM in May 2025 (10 crashes). Crashes on weekdays generally decreased, while Saturday crashes increased by 10, from 9 in May 2024 to 19 in May 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased from one in May 2024 to zero in May 2025, resulting in a fatal crash rate reduction from 0.95% to 0%. Serious injury crashes (severity 'A') decreased from 5 (4.8% of crashes) in May 2024 to 3 (4.1% of crashes) in May 2025. Minor injury crashes (severity 'B') also saw a reduction from 17 (16.2% of crashes) to 10 (13.5% of crashes) year-over-year.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes4.1%
↓-40.0%prior 5
Minor Injury10minor injury crashes13.5%
↓-41.2%prior 17
Possible Injury6possible injury crashes8.1%
→0.0%prior 6
No Injury55no injury crashes74.3%
↓-25.7%prior 74

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'Inattention' decreased by 7, from 24 in May 2024 to 17 in May 2025, representing a 29.2% drop in count. Conversely, 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' increased by 4 crashes, from 7 in May 2024 to 11 in May 2025, a 57.1% rise in count. The count for 'Failed to yield right of way' remained stable at 9 crashes in both periods.

Officer-Reported Primary Contributing Cause

Inattention17 (23%)↓-29.2%prior 24
No improper driving16 (21.6%)↓-11.1%prior 18
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner11 (14.9%)↑57.1%prior 7
Failed to yield right of way9 (12.2%)→0.0%prior 9
Followed too closely5 (6.8%)↓-28.6%prior 7
Visibility obstructed3 (4.1%)
Operating defective equipment3 (4.1%)
Distracted2 (2.7%)
Failure to keep in proper lane or running off road2 (2.7%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased by 30, from 77 in May 2024 to 47 in May 2025. Crashes during 'Daylight' conditions also saw a significant reduction of 35, from 85 in May 2024 to 50 in May 2025. There was an increase of 4 crashes occurring during 'Dusk' conditions, from 1 in May 2024 to 5 in May 2025.

Weather

Clear47 (63.5%)
↓-39.0%prior 77
Cloudy10 (13.5%)
Rain7 (9.5%)
↓-36.4%prior 11
Clear/Clear4 (5.4%)
Cloudy/Rain3 (4.1%)
↓-40.0%prior 5
Rain/Cloudy2 (2.7%)
Rain/Rain1 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash

Lighting

Daylight50 (67.6%)
↓-41.2%prior 85
Dark - lighted roadway11 (14.9%)
↓-8.3%prior 12
Dark - roadway not lighted5 (6.8%)
→0.0%prior 5
Dusk5 (6.8%)
Dark - unknown roadway lighting2 (2.7%)
Dawn1 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field

Road Surface

Dry59 (79.7%)
↓-28.0%prior 82
Wet14 (18.9%)
↓-33.3%prior 21
Sand, mud, dirt, oil, gravel1 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 191 in May 2024 to 135 in May 2025. Toyota and Ford remained the top two vehicle makes involved, though their counts decreased from 26 to 22 for Toyota and 26 to 21 for Ford. The age group '26-34' saw the largest decrease in persons involved, dropping from 48 in May 2024 to 19 in May 2025.

Top Vehicle Makes (135 vehicles)

1
TOYOTA22 (16.3%)
↓-15.4%prior 26
2
FORD21 (15.6%)
↓-19.2%prior 26
3
NISSAN13 (9.6%)
↓-13.3%prior 15
4
JEEP11 (8.1%)
↓-15.4%prior 13
5
CHEVROLET11 (8.1%)
↓-8.3%prior 12
6
HONDA8 (5.9%)
↓-57.9%prior 19
7
SUBARU7 (5.2%)
→0.0%prior 7
8
RAM5 (3.7%)
9
LEXUS4 (3%)
10
HYUNDAI3 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records

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

Sex Distribution (160 persons with recorded sex)

Male82 (51.2%)
↓-40.1%prior 137
Female78 (48.8%)
↓-28.4%prior 109

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone decreased by 9, from 33 in May 2024 to 24 in May 2025. Similarly, crashes in the 40 mph zone decreased by 5, from 15 to 10. The 60 mph speed zone saw a decrease of 5 crashes, from 14 in May 2024 (which included 1 fatal crash) to 9 in May 2025 (with 0 fatal crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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: 2025-05-01 through 2025-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-05-01 through 2025-05-31 (31 days)
  • Geographic scope: PLYMOUTH, MA
  • Total crash records analyzed: 74
  • Total persons involved: 172
  • Total vehicles involved: 135

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: May 2025." Published June 21, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/plymouth/may-2025-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 — May 2025 | ThatCarHitMe.com