Monthly Traffic Safety Analysis

31 CRASHES IN
WALPOLE, MA
SEPTEMBER 2025

All metrics benchmarked againstSeptember 2024

In Walpole, September 2025 saw a total of 31 crashes, a decrease of 13.89% compared to the 36 crashes reported in September 2024. Total injuries also decreased from 6 to 5. One notable shift was the increase in hit-and-run crashes, which rose from 2 incidents to 3, with the hit-and-run rate increasing from 5.6% to 9.7%.

31

-13.9%was 36

Total Crash Events

0

Persons Killed

5

-16.7%was 6

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a decrease in crash incidents year-over-year, with total crashes falling from 36 in September 2024 to 31 in September 2025, representing a 13.89% reduction. Concurrently, total injuries decreased by 16.67%, from 6 to 5, while total fatalities remained at 0 in both periods.

3

Hit-and-Run Crashes — September 2025

50.0% vs prior (2)

Hit-and-run crashes increased from 2 incidents in September 2024 to 3 incidents in September 2025. This change also led to an increase in the hit-and-run rate, rising from 5.6% of total crashes in the prior period to 9.7% in the current period.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

4

Motorists Injured

Prior: 5-20.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Friday in September 2024 (7 crashes) to Thursday in September 2025 (6 crashes), though Sunday and Wednesday also recorded 6 crashes in the current period. The peak hour for crashes moved from 4 p.m. (5 crashes) in the prior year to 5 p.m. (5 crashes) in the current year. There was a notable decrease in crashes on Fridays, from 7 to 3, and an increase on Wednesdays and Thursdays, both rising from 4 to 6 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes or fatalities in either September 2024 or September 2025. Total injuries decreased from 6 to 5 year-over-year. Minor injuries increased from 1 crash (2.8% share) in the prior period to 3 crashes (9.7% share) in the current period, while possible injuries decreased from 3 crashes (8.3% share) to 1 crash (3.2% share).

Outcome by Severity (Crash Events)

Minor Injury3minor injury crashes9.7%
200.0%prior 1
Possible Injury1possible injury crashes3.2%
-66.7%prior 3
No Injury26no injury crashes83.9%
-18.8%prior 32

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'No improper driving' remained consistent with 10 crashes in both periods. Crashes attributed to 'Disregarded traffic signs, signals, road markings' increased from 1 to 4, and 'Inattention' increased from 2 to 4 crashes. Conversely, 'Failed to yield right of way' decreased significantly from 6 crashes to 1, and 'Followed too closely' dropped from 6 crashes to 2.

Officer-Reported Primary Contributing Cause

No improper driving10 (32.3%)0.0%prior 10
Disregarded traffic signs, signals, road markings4 (12.9%)
Inattention4 (12.9%)
Made an improper turn2 (6.5%)
Followed too closely2 (6.5%)-66.7%prior 6
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (3.2%)
Other improper action1 (3.2%)
Failed to yield right of way1 (3.2%)-83.3%prior 6
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (3.2%)
Emotional1 (3.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

In both periods, the majority of crashes occurred in 'Daylight' conditions, decreasing slightly from 29 to 26 incidents. 'Clear' weather was the most common condition, though the count decreased from 29 to 23 crashes. The number of crashes occurring on 'Wet' road surfaces remained stable at 3 incidents in both September 2024 and September 2025.

Weather

Clear23 (76.7%)
-20.7%prior 29
Clear/Clear3 (10.0%)
Cloudy2 (6.7%)
Clear/Cloudy1 (3.3%)
Rain1 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Weather condition at time of crash

Lighting

Daylight26 (83.9%)
-10.3%prior 29
Dark - lighted roadway4 (12.9%)
Dusk1 (3.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Lighting condition field

Road Surface

Dry27 (90.0%)
-18.2%prior 33
Wet3 (10.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 72 in September 2024 to 57 in September 2025. The representation of vehicle makes saw shifts, with JEEP increasing from 2 to 6 vehicles and SUBARU increasing from 1 to 5 vehicles. Regarding persons involved, the number of males decreased from 51 to 31, while the number of females remained stable at 33. The age group 35-44 saw a significant decrease in persons involved, from 18 to 3.

Top Vehicle Makes (57 vehicles)

1
TOYOTA13 (22.8%)
-7.1%prior 14
2
JEEP6 (10.5%)
3
SUBARU5 (8.8%)
4
FORD5 (8.8%)
-16.7%prior 6
5
HONDA4 (7%)
-42.9%prior 7
6
CHEVROLET4 (7%)
-20.0%prior 5
7
MERCEDES-BENZ3 (5.3%)
8
NISSAN2 (3.5%)
9
ACURA2 (3.5%)
10
HYUNDAI2 (3.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Vehicle unit records

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

Sex Distribution (64 persons with recorded sex)

Female33 (51.6%)
0.0%prior 33
Male31 (48.4%)
-39.2%prior 51

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones decreased from 16 to 12, and those in 35 mph zones decreased from 8 to 4. Conversely, crashes in 45 mph zones increased from 2 to 4. New occurrences were noted in 25 mph zones (2 crashes) and 50 mph zones (2 crashes) in September 2025, which had no recorded crashes in September 2024. There were no fatal crashes recorded in any speed zone in either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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: 2025-09-01 through 2025-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-09-01 through 2025-09-30 (30 days)
  • Geographic scope: WALPOLE, MA
  • Total crash records analyzed: 31
  • Total persons involved: 70
  • Total vehicles involved: 57

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: September 2025." Published June 21, 2026. Reporting period: 2025-09-01 to 2025-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/walpole/september-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 — September 2025 | ThatCarHitMe.com