Monthly Traffic Safety Analysis

40 CRASHES IN
WALPOLE, MA
MARCH 2025

All metrics benchmarked againstMarch 2024

Total crashes in Walpole increased from 33 in March 2024 to 40 in March 2025, a 21.21% rise. A notable positive shift was the complete absence of DUI-related crashes in the current period, down from 2 in the prior year.

40

21.2%was 33

Total Crash Events

0

Persons Killed

7

40.0%was 5

Persons Injured

3

50.0%was 2

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 · 2025-03-01 to 2025-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Walpole increased year-over-year, with total crashes rising by 21.21% from 33 to 40. Similarly, total injuries saw a 40% increase, going from 5 to 7.

3

Hit-and-Run Crashes — March 2025

50.0% vs prior (2)

Hit-and-run crashes increased from 2 in March 2024 to 3 in March 2025, representing a 50% rise in count. The hit-and-run rate also increased from 6.1% to 7.5% of all crashes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

7

Motorists Injured

Prior: 540.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Friday in both periods, with counts increasing from 8 to 10. The peak crash hour shifted from 2 PM in the prior period to 3 PM in the current period, with both hours recording 4 crashes. Monday and Thursday saw notable increases in crash counts, rising from 2 to 9 and 2 to 6 respectively.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While both periods reported zero fatalities, total injuries increased by 40%, from 5 in March 2024 to 7 in March 2025. The current period also saw one serious injury crash, compared to none in the prior period, alongside an increase in minor injury crashes from 2 to 3.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.5%
Minor Injury3minor injury crashes7.5%
50.0%prior 2
Possible Injury2possible injury crashes5%
-33.3%prior 3
No Injury34no injury crashes85%
25.9%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Most severe injury per crash record

Top Contributing Factors

The most significant change in contributing factors was 'Failed to yield right of way,' which increased by 5 crashes, from 2 in the prior period to 7 in the current period. Conversely, 'No improper driving' decreased by 2 crashes, from 12 to 10, and 'Failure to keep in proper lane or running off road' also decreased by 2 crashes, from 5 to 3.

Officer-Reported Primary Contributing Cause

No improper driving10 (25%)-16.7%prior 12
Failed to yield right of way7 (17.5%)
Followed too closely4 (10%)
Inattention4 (10%)
Failure to keep in proper lane or running off road3 (7.5%)-40.0%prior 5
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway3 (7.5%)
Disregarded traffic signs, signals, road markings2 (5%)
Made an improper turn2 (5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (5%)
Other improper action2 (5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in daylight conditions increased significantly, rising from 20 in March 2024 to 35 in March 2025. Concurrently, crashes in dark-lighted roadway conditions decreased from 11 to 5. The number of crashes occurring in clear weather conditions increased from 23 to 30, while crashes in wet road conditions remained stable at 6.

Weather

Clear30 (75.0%)
30.4%prior 23
Rain4 (10.0%)
Cloudy3 (7.5%)
Clear/Clear1 (2.5%)
Clear/Unknown1 (2.5%)
Severe crosswinds1 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Weather condition at time of crash

Lighting

Daylight35 (87.5%)
75.0%prior 20
Dark - lighted roadway5 (12.5%)
-54.5%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Lighting condition field

Road Surface

Dry34 (85.0%)
25.9%prior 27
Wet6 (15.0%)
0.0%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 58 to 73 year-over-year. A notable shift in age distribution was observed in the 26-34 age group, which saw an increase from 5 to 17 persons involved, while the 35-44 age group decreased from 16 to 7 persons involved. Toyota and Ford remained the top two vehicle makes involved, with Jeep showing a significant increase from 1 to 6 vehicles involved.

Top Vehicle Makes (73 vehicles)

1
TOYOTA16 (21.9%)
14.3%prior 14
2
FORD13 (17.8%)
85.7%prior 7
3
JEEP6 (8.2%)
4
HONDA6 (8.2%)
5
CHEVROLET5 (6.8%)
6
FRHT3 (4.1%)
7
NISSAN3 (4.1%)
8
DODGE2 (2.7%)
9
RAM2 (2.7%)
10
TESL1 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Vehicle unit records

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

Sex Distribution (84 persons with recorded sex)

Female43 (51.2%)
13.2%prior 38
Male41 (48.8%)
2.5%prior 40

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Person-level records linked to crash events

Speed Limit Zones

The 30 mph speed zone continued to have the highest number of crashes, increasing from 14 to 15. Crashes in the 35 mph zone also increased from 6 to 9. Additionally, 2 crashes occurred in the 50 mph speed zone in the current period, a category not present in the prior period's data, with no fatalities reported in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · 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: 2025-03-01 through 2025-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-03-01 through 2025-03-31 (31 days)
  • Geographic scope: WALPOLE, MA
  • Total crash records analyzed: 40
  • Total persons involved: 92
  • Total vehicles involved: 73

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). "WALPOLE, MA Crash Intelligence Report: March 2025." Published June 21, 2026. Reporting period: 2025-03-01 to 2025-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/walpole/march-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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Walpole, MA Crash Report — March 2025 | ThatCarHitMe.com