Monthly Traffic Safety Analysis

54 CRASHES IN
WALPOLE, MA
DECEMBER 2024

All metrics benchmarked againstDecember 2023

WALPOLE, MA experienced an increase in total crashes in December 2024 compared to December 2023, with 54 crashes versus 47 crashes, marking a 14.9% rise. Concurrently, total injuries increased by 21.4%, from 14 injured persons in the prior period to 17 in the current period. This indicates a notable increase in both crash frequency and associated injuries year-over-year.

54

14.9%was 47

Total Crash Events

0

Persons Killed

17

21.4%was 14

Persons Injured

2

-33.3%was 3

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 · 2024-12-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in WALPOLE, MA trended upwards in December 2024 compared to the previous year. Total crashes increased by 14.9%, rising from 47 to 54, while total injuries saw a 21.4% increase, from 14 to 17 injured persons.

2

Hit-and-Run Crashes — December 2024

-33.3% vs prior (3)

Hit-and-run crashes decreased from 3 incidents in December 2023 to 2 incidents in December 2024. This resulted in a reduction of the hit-and-run rate from 6.4% to 3.7% of total crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 10.0%

16

Motorists Injured

Prior: 1323.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · 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 significantly year-over-year. In December 2024, Friday became the peak day for crashes with 21 incidents, a change from Saturday being the peak day with 12 crashes in December 2023. The peak crash hour also shifted from 8 PM (6 crashes) in the prior period to 6 PM (8 crashes) in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either December 2024 or December 2023. Total injuries increased by 21.4%, from 14 persons in the prior period to 17 persons in the current period. While crashes resulting in serious injuries increased from 2 to 3, crashes with minor injuries decreased from 5 to 4.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes5.6%
50.0%prior 2
Minor Injury4minor injury crashes7.4%
-20.0%prior 5
Possible Injury3possible injury crashes5.6%
-25.0%prior 4
No Injury44no injury crashes81.5%
22.2%prior 36

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, "No improper driving," saw an 84.6% increase, rising from 13 instances in December 2023 to 24 in December 2024. Conversely, "Failed to yield right of way" decreased by 50%, from 10 instances to 5. "Inattention" also saw a slight decrease, from 4 instances to 3.

Officer-Reported Primary Contributing Cause

No improper driving24 (44.4%)84.6%prior 13
Failed to yield right of way5 (9.3%)-50.0%prior 10
Failure to keep in proper lane or running off road4 (7.4%)
Inattention3 (5.6%)
Driving too fast for conditions3 (5.6%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (3.7%)
Other improper action2 (3.7%)
Disregarded traffic signs, signals, road markings1 (1.9%)
Visibility obstructed1 (1.9%)
Followed too closely1 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Adverse weather conditions played a more prominent role in December 2024, with 10 crashes occurring in snowy weather and 12 on snowy road surfaces, neither of which were top conditions in December 2023. Crashes on dry road surfaces decreased from 36 to 32, while crashes during daylight hours increased from 20 to 28. Crashes in rainy conditions decreased from 6 to 2.

Weather

Clear24 (44.4%)
-17.2%prior 29
Snow10 (18.5%)
Cloudy7 (13.0%)
Cloudy/Rain2 (3.7%)
Cloudy/Snow2 (3.7%)
Rain2 (3.7%)
-66.7%prior 6
Snow/Sleet, hail (freezing rain or drizzle)2 (3.7%)
Clear/Clear2 (3.7%)
Clear/Cloudy2 (3.7%)
Fog, smog, smoke1 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight28 (51.9%)
40.0%prior 20
Dark - lighted roadway19 (35.2%)
18.8%prior 16
Dark - roadway not lighted4 (7.4%)
-42.9%prior 7
Dusk2 (3.7%)
Dawn1 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry32 (60.4%)
-11.1%prior 36
Snow12 (22.6%)
Wet7 (13.2%)
-22.2%prior 9
Ice2 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 80 to 97 year-over-year. While Honda vehicles involved in crashes increased from 13 to 17, Toyota saw a slight decrease from 14 to 12. Notably, Nissan vehicles involved in crashes increased from 3 to 10.

Top Vehicle Makes (97 vehicles)

1
HONDA17 (17.5%)
30.8%prior 13
2
TOYOTA12 (12.4%)
-14.3%prior 14
3
NISSAN10 (10.3%)
4
FORD10 (10.3%)
11.1%prior 9
5
CHEVROLET8 (8.2%)
-11.1%prior 9
6
JEEP6 (6.2%)
7
SUBARU4 (4.1%)
8
ACURA3 (3.1%)
9
LEXUS3 (3.1%)
10
MERCEDES-BENZ3 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (112 persons with recorded sex)

Male57 (50.9%)
-1.7%prior 58
Female55 (49.1%)
41.0%prior 39

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone increased from 24 in December 2023 to 26 in December 2024. Conversely, crashes in the 65 mph speed zone decreased from 7 to 3. There were no fatal crashes reported across any speed zone in either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · 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: 2024-12-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-12-01 through 2024-12-31 (31 days)
  • Geographic scope: WALPOLE, MA
  • Total crash records analyzed: 54
  • Total persons involved: 117
  • Total vehicles involved: 97

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: December 2024." Published June 21, 2026. Reporting period: 2024-12-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/walpole/december-2024-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 — December 2024 | ThatCarHitMe.com