Monthly Traffic Safety Analysis

9 CRASHES IN
PLYMPTON, MA
FEBRUARY 2026

All metrics benchmarked againstFebruary 2025

In February 2026, Plympton experienced 9 total crashes, marking a 50% increase compared to the 6 crashes recorded in February 2025. A notable shift is the rise in injuries, with 4 persons injured in the current period compared to zero in the prior period. Additionally, one DUI crash was reported in February 2026, while none occurred in the same month last year.

9

50.0%was 6

Total Crash Events

0

Persons Killed

4

Persons Injured

0

Fatal Crash Events

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 · 2026-02-01 to 2026-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in Plympton shows an upward trend year-over-year, with total crashes increasing by 50% from 6 in February 2025 to 9 in February 2026. This period also saw an increase in injuries, rising from zero in the prior year to 4 in the current period, while fatalities remained at zero for both months.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

4

Motorists Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between the two periods. In February 2026, the peak day for crashes was Thursday with 4 incidents, a change from February 2025 where Monday was the peak day with 3 crashes. The peak hour also moved, with 2 crashes occurring at 6p in the current period, whereas the prior period's peak was 9p with 1 crash.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Outcome by Severity (Crash Events)

Minor Injury2minor injury crashes22.2%
Possible Injury1possible injury crashes11.1%
No Injury6no injury crashes66.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Most severe injury per crash record

Top Contributing Factors

Analysis of contributing factors reveals shifts in crash causation. 'Failure to keep in proper lane or running off road' saw a significant increase, rising from 1 crash in February 2025 to 3 crashes in February 2026. While 'No improper driving' remained a leading factor, its count increased from 3 to 4 crashes year-over-year. Factors such as 'Followed too closely' and 'Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway' each contributed to 1 crash in the current period, not being present in the prior year's data.

Officer-Reported Primary Contributing Cause

No improper driving4 (44.4%)
Failure to keep in proper lane or running off road3 (33.3%)
Followed too closely1 (11.1%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions show some changes year-over-year. Crashes occurring in clear weather decreased slightly from 5 in February 2025 to 4 in February 2026, with the current period showing a greater diversity of weather conditions including rain and snow. Regarding lighting, daylight crashes decreased from 4 to 3, while crashes in 'Dark - lighted roadway' and 'Dark - roadway not lighted' each increased from 1 to 2 incidents. On road surfaces, dry condition crashes increased from 3 to 4, and wet condition crashes rose from 2 to 3, with snow-related crashes appearing in the current period.

Weather

Clear4 (44.4%)
-20.0%prior 5
Clear/Cloudy1 (11.1%)
Cloudy1 (11.1%)
Rain1 (11.1%)
Snow1 (11.1%)
Snow/Sleet, hail (freezing rain or drizzle)1 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Weather condition at time of crash

Lighting

Daylight3 (33.3%)
Dark - lighted roadway2 (22.2%)
Dark - roadway not lighted2 (22.2%)
Dark - unknown roadway lighting1 (11.1%)
Dusk1 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Lighting condition field

Road Surface

Dry4 (44.4%)
Wet3 (33.3%)
Snow2 (22.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (14 vehicles)

1
CHEVROLET4 (28.6%)
2
HONDA3 (21.4%)
3
FORD2 (14.3%)
4
TOYOTA2 (14.3%)
5
CHRYSLER1 (7.1%)
6
HYUNDAI1 (7.1%)
7
SUBARU1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Vehicle unit records

Sex Distribution (15 persons with recorded sex)

Male8 (53.3%)
166.7%prior 3
Female7 (46.7%)
75.0%prior 4

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed limit zones changed between the two periods. Crashes occurring in 30 mph zones increased from 1 in February 2025 to 2 in February 2026. The current period saw crashes reported in 10, 25, 40, and 45 mph zones, which were not present in the prior year's data. Conversely, crashes in 35, 55, and 65 mph zones, present in February 2025, were not reported in February 2026. No fatalities were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · 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: 2026-02-01 through 2026-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2026-02-01 through 2026-02-28 (28 days)
  • Geographic scope: PLYMPTON, MA
  • Total crash records analyzed: 9
  • Total persons involved: 15
  • Total vehicles involved: 14

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). "PLYMPTON, MA Crash Intelligence Report: February 2026." Published June 21, 2026. Reporting period: 2026-02-01 to 2026-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/plympton/february-2026-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

ThatCarHitMe.com · An Injuria.ai Company

Plympton, MA Crash Report — February 2026 | ThatCarHitMe.com