Monthly Traffic Safety Analysis

50 CRASHES IN
CANTON, MA
DECEMBER 2025

All metrics benchmarked againstDecember 2024

In December 2025, Canton, MA experienced 50 total crashes, a decrease of 29.6% compared to the 71 crashes reported in December 2024. This period saw no fatalities, a reduction from the 1 fatality recorded in the prior year. Total injuries slightly increased from 24 to 25.

50

-29.6%was 71

Total Crash Events

0

-100.0%was 1

Persons Killed

25

4.2%was 24

Persons Injured

3

-50.0%was 6

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 · 2025-12-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash activity in Canton, MA trended downward in December 2025, with a 29.6% decrease in total crashes, from 71 to 50. Fatalities also saw a significant reduction, dropping from 1 in December 2024 to 0 in December 2025. Conversely, total injuries increased slightly by 4.2%, from 24 to 25.

3

Hit-and-Run Crashes — December 2025

-50.0% vs prior (6)

Hit-and-run crashes decreased by 50% year-over-year, from 6 incidents in December 2024 to 3 in December 2025. Consequently, the hit-and-run rate also decreased from 8.5% of total crashes in the prior period to 6% in the current period. This indicates a downward trend in hit-and-run incidents.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1-100.0%

25

Motorists Injured

Prior: 244.2%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Saturday in both periods, with 13 crashes in December 2025 and 14 in December 2024. However, the peak hour shifted from 1 PM in December 2024, which recorded 6 crashes, to 6 PM in December 2025, with 5 crashes. This indicates a shift in the most crash-prone hour from early afternoon to early evening.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased from 1 in December 2024 to 0 in December 2025. Serious injuries remained constant at 1 in both periods. Minor injuries increased from 6 in the prior period to 10 in the current period, while possible injuries decreased from 6 to 3.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2%
0.0%prior 1
Minor Injury10minor injury crashes20%
66.7%prior 6
Possible Injury3possible injury crashes6%
-50.0%prior 6
No Injury36no injury crashes72%
-36.8%prior 57

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

The most frequent contributing factor, 'No improper driving', decreased by 9 crashes, from 23 in December 2024 to 14 in December 2025. 'Followed too closely' remained constant at 7 crashes in both periods. 'Failed to yield right of way' decreased by 2 crashes, from 6 to 4, while 'Inattention' increased by 2 crashes, from 1 to 3.

Officer-Reported Primary Contributing Cause

No improper driving14 (28%)-39.1%prior 23
Followed too closely7 (14%)0.0%prior 7
Failed to yield right of way4 (8%)-33.3%prior 6
Inattention3 (6%)
Failure to keep in proper lane or running off road3 (6%)-40.0%prior 5
Made an improper turn2 (4%)
Driving too fast for conditions2 (4%)
Other improper action2 (4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2%)
Glare1 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 45 in December 2024 to 37 in December 2025. Crashes on 'Dry' road surfaces also decreased from 42 to 37 year-over-year. The number of crashes occurring during 'Daylight' hours decreased from 38 to 25, while crashes in 'Dark - lighted roadway' conditions decreased from 22 to 14.

Weather

Clear22 (44.9%)
-37.1%prior 35
Clear/Clear15 (30.6%)
87.5%prior 8
Cloudy3 (6.1%)
-50.0%prior 6
Snow/Sleet, hail (freezing rain or drizzle)2 (4.1%)
Cloudy/Cloudy1 (2.0%)
Cloudy/Rain1 (2.0%)
Rain/Severe crosswinds1 (2.0%)
Snow1 (2.0%)
-83.3%prior 6
Snow/Other1 (2.0%)
Snow/Severe crosswinds1 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight25 (50.0%)
-34.2%prior 38
Dark - lighted roadway14 (28.0%)
-36.4%prior 22
Dark - roadway not lighted6 (12.0%)
-25.0%prior 8
Dawn2 (4.0%)
Dusk2 (4.0%)
Dark - unknown roadway lighting1 (2.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry37 (75.5%)
-11.9%prior 42
Snow5 (10.2%)
-37.5%prior 8
Wet4 (8.2%)
-78.9%prior 19
Ice3 (6.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 130 in December 2024 to 96 in December 2025. Toyota, which was the top make in December 2024 with 19 vehicles, was surpassed by Honda in December 2025, which had 16 vehicles. Nissan dropped from 12 vehicles in December 2024 to 6 in December 2025, while Chevrolet decreased from 11 to 7.

Top Vehicle Makes (96 vehicles)

1
HONDA16 (16.7%)
33.3%prior 12
2
TOYOTA13 (13.5%)
-31.6%prior 19
3
FORD8 (8.3%)
-27.3%prior 11
4
CHEVROLET7 (7.3%)
-36.4%prior 11
5
NISSAN6 (6.3%)
-50.0%prior 12
6
MERCEDES-BENZ5 (5.2%)
0.0%prior 5
7
JEEP4 (4.2%)
-60.0%prior 10
8
VOLKSWAGEN3 (3.1%)
9
GMC3 (3.1%)
10
HYUNDAI3 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (119 persons with recorded sex)

Male68 (57.1%)
-20.0%prior 85
Female51 (42.9%)
-22.7%prior 66

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

The total number of crashes with recorded speed limits decreased from 68 in December 2024 to 44 in December 2025. Crashes in the 55 MPH speed zone increased from 3 to 11, while crashes in the 25 MPH zone decreased from 13 to 7. The prior period recorded 1 fatal crash in the 55 MPH zone, whereas no fatalities were recorded in any speed zone in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 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: 2025-12-01 through 2025-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-12-01 through 2025-12-31 (31 days)
  • Geographic scope: CANTON, MA
  • Total crash records analyzed: 50
  • Total persons involved: 127
  • Total vehicles involved: 96

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). "CANTON, MA Crash Intelligence Report: December 2025." Published June 21, 2026. Reporting period: 2025-12-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/canton/december-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

ThatCarHitMe.com · An Injuria.ai Company