Yearly Traffic Safety Analysis

963 CRASHES IN
PLYMOUTH, MA
2024

All metrics benchmarked against2023

In 2024, Plymouth recorded 963 total traffic crashes, an increase from the 881 crashes documented in 2023, representing a 9.3% rise. The most significant year-over-year change was the number of fatalities, which increased from 1 in 2023 to 5 in 2024.

963

9.3%was 881

Total Crash Events

5

400.0%was 1

Persons Killed

367

14.0%was 322

Persons Injured

69

176.0%was 25

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. 22 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic safety trends in Plymouth worsened from 2023 to 2024. Total crashes increased by 9.3%, from 881 to 963. Similarly, the number of people injured rose by 14.0% from 322 to 367, and fatalities increased from 1 to 5.

69

Hit-and-Run Crashes — 2024

176.0% vs prior (25)

Hit-and-run incidents increased substantially from 2023 to 2024. The number of hit-and-run crashes rose from 25 to 69, a 176% increase. This upward trend is also reflected in the hit-and-run rate, which climbed from 2.8% of all crashes in 2023 to 7.2% in 2024.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

5

Motorists Killed

Prior: 1400.0%

0

Other Killed

Prior: 00.0%

11

Pedestrians Injured

Prior: 4175.0%

10

Cyclists Injured

Prior: 742.9%

343

Motorists Injured

Prior: 31010.6%

3

Other Injured

Prior: 1200.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes shifted between the two periods. In 2024, the peak days for crashes were Friday and Saturday, each with 150 incidents, a change from 2023 when Wednesday and Thursday were the busiest days with 135 crashes each. The peak hour for collisions also moved earlier, from 4 p.m. in 2023 (72 crashes) to 2 p.m. in 2024 (81 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased from 2023 to 2024. The number of fatal crashes rose from 1 to 5, and the corresponding fatal crash rate increased from 0.11% to 0.52%. The proportion of crashes resulting in any injury also grew, with serious injuries accounting for 2.4% of crashes in 2024 compared to 2.2% in 2023. Consequently, the share of crashes with no reported injuries decreased from 72.1% in 2023 to 68.8% in 2024.

Outcome by Severity (Crash Events)

Fatal5fatal crashes0.5%
400.0%prior 1
Serious Injury23serious injury crashes2.4%
21.1%prior 19
Minor Injury172minor injury crashes17.9%
13.9%prior 151
Possible Injury78possible injury crashes8.1%
25.8%prior 62
No Injury663no injury crashes68.8%
4.4%prior 635

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

In both years, 'Inattention' was the leading contributing factor, with its count increasing by 13.0% from 169 incidents in 2023 to 191 in 2024. Crashes attributed to 'No improper driving' saw a significant 54.2% increase in count, from 107 in 2023 to 165 in 2024, moving it from the third to the second-ranked factor. Crashes involving 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' also increased in count by 24.2% from 66 to 82.

Officer-Reported Primary Contributing Cause

Inattention191 (19.8%)13.0%prior 169
No improper driving165 (17.1%)54.2%prior 107
Failed to yield right of way121 (12.6%)8.0%prior 112
Followed too closely93 (9.7%)4.5%prior 89
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner82 (8.5%)24.2%prior 66
Failure to keep in proper lane or running off road35 (3.6%)12.9%prior 31
Other improper action33 (3.4%)22.2%prior 27
Driving too fast for conditions27 (2.8%)-28.9%prior 38
Visibility obstructed26 (2.7%)36.8%prior 19
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway25 (2.6%)-37.5%prior 40

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of environmental conditions during crashes remained largely consistent between 2023 and 2024. In both periods, crashes predominantly occurred in 'Daylight' (65.0% of crashes in 2024 vs. 67.0% in 2023) on 'Dry' road surfaces (76.7% in 2024 vs. 76.0% in 2023). The proportion of crashes during 'Clear' weather was also stable, at 71.4% in 2024 compared to 70.9% in 2023, indicating no significant shift in crashes related to adverse conditions.

Weather

Clear688 (72.4%)
10.1%prior 625
Rain78 (8.2%)
9.9%prior 71
Cloudy68 (7.2%)
4.6%prior 65
Cloudy/Rain34 (3.6%)
6.3%prior 32
Clear/Clear16 (1.7%)
Snow13 (1.4%)
-23.5%prior 17
Rain/Cloudy12 (1.3%)
0.0%prior 12
Sleet, hail (freezing rain or drizzle)9 (0.9%)
Clear/Cloudy7 (0.7%)
0.0%prior 7
Snow/Blowing sand, snow3 (0.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight626 (65.3%)
6.1%prior 590
Dark - lighted roadway150 (15.6%)
5.6%prior 142
Dark - roadway not lighted110 (11.5%)
17.0%prior 94
Dusk43 (4.5%)
30.3%prior 33
Dawn26 (2.7%)
23.8%prior 21
Dark - unknown roadway lighting4 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry739 (76.9%)
10.5%prior 669
Wet177 (18.4%)
4.1%prior 170
Snow17 (1.8%)
-10.5%prior 19
Sand, mud, dirt, oil, gravel16 (1.7%)
128.6%prior 7
Slush5 (0.5%)
0.0%prior 5
Ice4 (0.4%)
-60.0%prior 10
Water (standing, moving)2 (0.2%)
Other1 (0.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained Toyota, Ford, and Honda in both 2023 and 2024, with only minor changes in their rankings. When examining the age of persons involved in collisions, there was an increase in the representation of the 26-34 age group, which grew from comprising 13.2% of individuals in 2023 to 15.6% in 2024. The proportional involvement of other age groups remained relatively stable.

Top Vehicle Makes (1,686 vehicles)

1
TOYOTA230 (13.6%)
-10.9%prior 258
2
FORD229 (13.6%)
13.4%prior 202
3
HONDA174 (10.3%)
9.4%prior 159
4
CHEVROLET137 (8.1%)
0.0%prior 137
5
JEEP99 (5.9%)
-9.2%prior 109
6
NISSAN91 (5.4%)
-9.9%prior 101
7
SUBARU80 (4.7%)
35.6%prior 59
8
HYUNDAI63 (3.7%)
6.8%prior 59
9
GMC54 (3.2%)
17.4%prior 46
10
KIA37 (2.2%)
15.6%prior 32

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (1,931 persons with recorded sex)

Male1,100 (57.0%)
5.6%prior 1,042
Female831 (43.0%)
-0.6%prior 836

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones showed some shifts, with incidents in 60 mph zones increasing from 120 to 130 year-over-year, while the number of crashes in 30 mph and 40 mph zones remained stable. A significant change was observed in the location of fatal crashes; in 2024, three of the five fatal crashes occurred in 60 mph zones, whereas the single fatal crash in 2023 occurred in a 35 mph zone.

Fatal crashes by zone: 30 mph: 1 of 302 (0.331%) · 40 mph: 1 of 132 (0.758%) · 60 mph: 3 of 130 (2.308%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: PLYMOUTH, MA
  • Total crash records analyzed: 963
  • Total persons involved: 2,116
  • Total vehicles involved: 1,686

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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/plymouth/2024-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 — 2024 | ThatCarHitMe.com