Monthly Traffic Safety Analysis

18 CRASHES IN
PLAINVILLE, MA
MARCH 2026

All metrics benchmarked againstMarch 2025

In March 2026, PLAINVILLE experienced 18 total crashes, a 28% decrease compared to the 25 crashes reported in March 2025. The most notable shift was the significant reduction in crashes attributed to "Inattention," which decreased by 6 crashes year-over-year.

18

-28.0%was 25

Total Crash Events

0

Persons Killed

6

-14.3%was 7

Persons Injured

1

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 · 2026-03-01 to 2026-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in PLAINVILLE showed a downward trend year-over-year, with total crashes decreasing by 28% from 25 in March 2025 to 18 in March 2026. This reduction also corresponded with a 14.3% decrease in total injuries, falling from 7 to 6 over the same period.

1

Hit-and-Run Crashes — March 2026

5.6% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

6

Motorists Injured

Prior: 7-14.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year. In March 2026, the peak day for crashes was Tuesday with 6 incidents, contrasting with March 2025 where Saturday and Sunday were tied for the peak with 5 crashes each. The peak hour also moved earlier in the day, from 3 p.m. with 4 crashes in March 2025 to 11 a.m. with 4 crashes in March 2026.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero in both March 2025 and March 2026. However, there was a slight decrease in overall injuries, from 7 in the prior period to 6 in the current period. While "Minor Injury" crashes decreased from 3 (12% share) to 2 (11.1% share), "Serious Injury" crashes increased from 0 to 1 (5.6% share) year-over-year.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes5.6%
Minor Injury2minor injury crashes11.1%
-33.3%prior 3
Possible Injury1possible injury crashes5.6%
-50.0%prior 2
No Injury14no injury crashes77.8%
-30.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Most severe injury per crash record

Top Contributing Factors

The distribution of contributing factors saw significant changes. "Inattention" crashes decreased by 66.7%, from 9 in March 2025 to 3 in March 2026, while "Failed to yield right of way" crashes decreased by 50%, from 6 to 3. Conversely, "No improper driving" crashes doubled in count, increasing from 2 to 4, and "Followed too closely" crashes rose from 0 to 2 year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving4 (22.2%)
Inattention3 (16.7%)-66.7%prior 9
Failed to yield right of way3 (16.7%)-50.0%prior 6
Followed too closely2 (11.1%)
Visibility obstructed1 (5.6%)
Driving too fast for conditions1 (5.6%)
Failure to keep in proper lane or running off road1 (5.6%)
Made an improper turn1 (5.6%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring on dry road surfaces significantly decreased from 19 in March 2025 to 9 in March 2026. Conversely, crashes on adverse road conditions like ice, slush, or snow, which were absent in March 2025, accounted for 3 crashes in March 2026. Crashes during daylight conditions saw a minor decrease from 17 to 15, while crashes in "Dark - lighted roadway" conditions decreased from 4 to 0.

Weather

Clear6 (35.3%)
-25.0%prior 8
Clear/Clear4 (23.5%)
-20.0%prior 5
Rain2 (11.8%)
Cloudy/Cloudy1 (5.9%)
Sleet, hail (freezing rain or drizzle)/Sleet, hail (freezing rain or drizzle)1 (5.9%)
Snow/Snow1 (5.9%)
Clear/Cloudy1 (5.9%)
Cloudy1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Weather condition at time of crash

Lighting

Daylight15 (83.3%)
-11.8%prior 17
Dark - roadway not lighted2 (11.1%)
Dusk1 (5.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Lighting condition field

Road Surface

Dry9 (56.3%)
-52.6%prior 19
Wet4 (25.0%)
-20.0%prior 5
Ice1 (6.3%)
Slush1 (6.3%)
Snow1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (37 vehicles)

1
TOYOTA5 (13.5%)
0.0%prior 5
2
JEEP5 (13.5%)
3
FORD4 (10.8%)
4
NISSAN3 (8.1%)
5
HYUNDAI3 (8.1%)
6
HONDA3 (8.1%)
-62.5%prior 8
7
RAM2 (5.4%)
8
SUBARU2 (5.4%)
9
CHEVROLET2 (5.4%)
10
VOLKSWAGEN1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Vehicle unit records

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

Sex Distribution (45 persons with recorded sex)

Male24 (53.3%)
-22.6%prior 31
Female21 (46.7%)
10.5%prior 19

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones decreased from 4 to 2, and those in 40 mph zones dropped from 6 to 1 year-over-year. In contrast, crashes in 55 mph zones increased from 1 to 2. Fatal crashes remained at zero across all speed zones in both periods.

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

Data Coverage

  • Reporting period: 2026-03-01 through 2026-03-31 (31 days)
  • Geographic scope: PLAINVILLE, MA
  • Total crash records analyzed: 18
  • Total persons involved: 49
  • Total vehicles involved: 37

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

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Plainville, MA Crash Report — March 2026 | ThatCarHitMe.com