Yearly Traffic Safety Analysis

877 CRASHES IN
PLYMOUTH, MA
2025

All metrics benchmarked against2024

In 2025, Plymouth recorded 877 total crashes, a decrease from the 963 crashes reported in 2024, representing an 8.9% year-over-year reduction. While overall crashes declined, one of the most significant changes was a 47.8% decrease in the number of hit-and-run incidents, which fell from 69 to 36. The number of fatalities remained stable at five for both periods.

877

-8.9%was 963

Total Crash Events

5

Persons Killed

317

-13.6%was 367

Persons Injured

36

-47.8%was 69

Hit-and-Run Crashes

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 12 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in Plymouth shows a decrease in traffic incidents from 2024 to 2025. Total crashes fell by 8.9%, from 963 to 877, and the number of people injured in these incidents decreased by 13.6% from 367 to 317. The number of fatalities remained unchanged at 5 for both years.

36

Hit-and-Run Crashes — 2025

-47.8% vs prior (69)

There was a significant year-over-year decrease in hit-and-run incidents in Plymouth. The total number of hit-and-run crashes fell by 47.8%, from 69 in 2024 to 36 in 2025. Consequently, the hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, dropped from 7.2% to 4.1%.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Cyclists Killed

Prior: 00.0%

4

Motorists Killed

Prior: 5-20.0%

0

Other Killed

Prior: 00.0%

9

Pedestrians Injured

Prior: 11-18.2%

6

Cyclists Injured

Prior: 10-40.0%

295

Motorists Injured

Prior: 343-14.0%

7

Other Injured

Prior: 3133.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes in Plymouth remained broadly consistent year-over-year, with incidents peaking during the afternoon and on weekends. The peak day for crashes in 2025 was Saturday with 139 incidents, compared to a tie between Friday and Saturday (150 crashes each) in 2024. The peak hour for crashes shifted slightly later in the afternoon, from 2 p.m. (81 crashes) in the prior year to 3 p.m. (74 crashes) in the current year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the number of fatal crashes remained constant at 5 for both periods, the fatal crash rate per 100 crashes increased from 0.52% to 0.57% due to the overall reduction in total incidents. The count of crashes involving serious injuries increased from 23 to 27, raising its share of all crashes from 2.4% to 3.1%. Crashes involving possible injuries saw a notable decrease, falling from 78 incidents (8.1% of total) to 48 incidents (5.5% of total).

Outcome by Severity (Crash Events)

Fatal5fatal crashes0.6%
0.0%prior 5
Serious Injury27serious injury crashes3.1%
17.4%prior 23
Minor Injury163minor injury crashes18.6%
-5.2%prior 172
Possible Injury48possible injury crashes5.5%
-38.5%prior 78
No Injury622no injury crashes70.9%
-6.2%prior 663

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

Inattention remained the top contributing factor in both periods, though its count decreased by 5.8% from 191 to 180 crashes. The ranking of the top three factors was unchanged, with 'Failed to yield right of way' and 'Followed too closely' also seeing their counts decrease. Notably, crashes attributed to 'Distracted' driving increased by 138.5% from 13 to 31 incidents, and crashes involving 'Swerving or avoiding' rose by 80% from 25 to 45 incidents.

Officer-Reported Primary Contributing Cause

Inattention180 (20.5%)-5.8%prior 191
No improper driving129 (14.7%)-21.8%prior 165
Failed to yield right of way103 (11.7%)-14.9%prior 121
Followed too closely84 (9.6%)-9.7%prior 93
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner62 (7.1%)-24.4%prior 82
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway45 (5.1%)80.0%prior 25
Failure to keep in proper lane or running off road44 (5%)25.7%prior 35
Distracted31 (3.5%)138.5%prior 13
Visibility obstructed28 (3.2%)7.7%prior 26
Driving too fast for conditions26 (3%)-3.7%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in both years predominantly occurred in clear weather and on dry roads, with these conditions accounting for the majority of incidents in both periods. There was a slight shift in lighting conditions, with the proportion of crashes occurring in daylight decreasing from 65.0% to 62.5% year-over-year. Correspondingly, crashes in dark conditions (both lighted and unlighted roadways) increased as a share of the total, from 27.0% in 2024 to 30.0% in 2025.

Weather

Clear557 (63.6%)
-19.0%prior 688
Clear/Clear103 (11.8%)
543.8%prior 16
Cloudy61 (7.0%)
-10.3%prior 68
Rain57 (6.5%)
-26.9%prior 78
Snow24 (2.7%)
84.6%prior 13
Cloudy/Rain14 (1.6%)
-58.8%prior 34
Rain/Rain11 (1.3%)
Rain/Cloudy9 (1.0%)
-25.0%prior 12
Clear/Cloudy7 (0.8%)
0.0%prior 7
Snow/Sleet, hail (freezing rain or drizzle)7 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight548 (62.6%)
-12.5%prior 626
Dark - lighted roadway157 (17.9%)
4.7%prior 150
Dark - roadway not lighted106 (12.1%)
-3.6%prior 110
Dusk43 (4.9%)
0.0%prior 43
Dawn16 (1.8%)
-38.5%prior 26
Dark - unknown roadway lighting6 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry682 (77.9%)
-7.7%prior 739
Wet133 (15.2%)
-24.9%prior 177
Snow30 (3.4%)
76.5%prior 17
Ice22 (2.5%)
Sand, mud, dirt, oil, gravel5 (0.6%)
-68.8%prior 16
Water (standing, moving)3 (0.3%)
Slush1 (0.1%)
-80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained Toyota, Ford, and Honda in both years. However, the number of Toyotas involved increased from 230 to 260, while Fords decreased from 229 to 196 and Hondas decreased from 174 to 145. The age distribution of persons involved in crashes showed minimal change across all brackets; for example, the 65+ age group represented 15.4% of individuals in the prior year and 15.8% in the current year.

Top Vehicle Makes (1,529 vehicles)

1
TOYOTA260 (17%)
13.0%prior 230
2
FORD196 (12.8%)
-14.4%prior 229
3
HONDA145 (9.5%)
-16.7%prior 174
4
CHEVROLET127 (8.3%)
-7.3%prior 137
5
NISSAN95 (6.2%)
4.4%prior 91
6
JEEP91 (6%)
-8.1%prior 99
7
SUBARU68 (4.4%)
-15.0%prior 80
8
HYUNDAI60 (3.9%)
-4.8%prior 63
9
GMC41 (2.7%)
-24.1%prior 54
10
KIA35 (2.3%)
-5.4%prior 37

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (1,775 persons with recorded sex)

Male988 (55.7%)
-10.2%prior 1,100
Female787 (44.3%)
-5.3%prior 831

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across different speed zones remained nearly identical year-over-year, with approximately 67% of incidents in both periods occurring in zones with speed limits below 40 mph. In 2024, three of the five fatal crashes occurred in 60 mph zones. In 2025, the five fatal crashes were more distributed across speed zones, with one incident each in 25, 30, 40, and 60 mph zones.

Fatal crashes by zone: 25 mph: 1 of 59 (1.695%) · 30 mph: 1 of 325 (0.308%) · 40 mph: 1 of 123 (0.813%) · 60 mph: 1 of 101 (0.99%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: PLYMOUTH, MA
  • Total crash records analyzed: 877
  • Total persons involved: 1,905
  • Total vehicles involved: 1,529

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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/plymouth/2025-annual-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 — 2025 | ThatCarHitMe.com