ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · WALPOLE, MA · 2025
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/walpole/2025-annual-report
Yearly Traffic Safety Analysis
415 CRASHES IN
WALPOLE, MA
2025
In Walpole, total traffic crashes decreased from 477 in the prior year to 415 in the current year, a 13.0% reduction. While overall crashes and injuries declined, the most notable year-over-year shift was the emergence of 3 fatal crashes in the current period, whereas none were recorded in the previous year. This resulted in 3 fatalities, a change from zero in the prior period.
415
▼ -13.0%was 477
Total Crash Events
3
Persons Killed
111
▼ -13.3%was 128
Persons Injured
15
▼ -31.8%was 22
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Walpole are heading downward year-over-year. Total crashes fell by 13.0%, from 477 to 415. Similarly, the number of people injured in these incidents decreased by 13.3%, from 128 to 111.
15
Hit-and-Run Crashes — 2025
▼ -31.8% vs prior (22)
Hit-and-run crashes showed a downward trend. The total number of hit-and-run incidents decreased from 22 in the prior year to 15 in the current year. This resulted in a corresponding drop in the hit-and-run rate from 4.6% of all crashes to 3.6%.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
1
Pedestrians Injured
2
Cyclists Injured
108
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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. The peak day for crashes moved from Friday (102 crashes) in the prior year to Thursday (68 crashes) in the current year. The peak hour also changed significantly, from the 4 p.m. afternoon commute hour (47 crashes) to the 7 a.m. morning commute hour (39 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While the total number of crashes decreased, the severity profile worsened with the introduction of fatal incidents. The current period saw 3 fatal crashes, accounting for 0.7% of all crashes, compared to zero fatal crashes in the prior period. The count of serious injury crashes decreased from 7 to 3, but the overall proportion of crashes involving any type of injury remained stable, moving from 19.5% to 20.7%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
The top three contributing factors were consistent across both years: 'No improper driving,' 'Inattention,' and 'Failed to yield right of way.' The count of crashes related to 'Inattention' fell from 68 to 53, a 22.1% decrease in count. In contrast, crashes where drivers 'Disregarded traffic signs, signals, road markings' increased in count from 14 to 23, a 64.3% rise.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions remained largely consistent year-over-year, with most incidents in both periods occurring in daylight on dry roads. The share of crashes happening in daylight increased slightly from 68.8% to 73.5%. Crashes on wet road surfaces accounted for a slightly higher proportion of the total, rising from 14.5% in the prior period to 16.9% in the current period.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
Toyota, Ford, and Honda were the top three vehicle makes involved in crashes in both periods, though Ford (84 vehicles) surpassed Honda (69 vehicles) for the second spot in the current year. Regarding persons involved, the share from the 35-44 age group decreased from 18.5% of the total in the prior year to 15.3% in the current year. The total number of vehicles involved in crashes decreased from 877 to 760.
Top Vehicle Makes (760 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
47 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (899 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph zone, the most frequent location for incidents in both periods, decreased from 198 to 155. A significant change was observed in the 40 mph zone, where all 3 of the current year's fatal crashes occurred. In the prior year, no fatal crashes were recorded in any speed zone.
Fatal crashes by zone: 40 mph: 3 of 49 (6.122%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: WALPOLE, MA
- Total crash records analyzed: 415
- Total persons involved: 945
- Total vehicles involved: 760
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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/walpole/2025-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved