Monthly Traffic Safety Analysis

13 CRASHES IN
NORTON, MA
JUNE 2025

All metrics benchmarked againstJune 2024

In June 2025, NORTON experienced 13 crashes, a significant decrease of 60.6% compared to the 33 crashes recorded in June 2024. This substantial reduction in overall incidents was accompanied by a notable decrease in total injuries, falling from 6 in the prior period to 1 in the current period.

13

-60.6%was 33

Total Crash Events

0

Persons Killed

1

-83.3%was 6

Persons Injured

0

-100.0%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 · 2025-06-01 to 2025-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, NORTON saw a significant downward trend in crashes, with a 60.6% reduction from 33 crashes in June 2024 to 13 crashes in June 2025. This indicates a notable improvement in traffic safety for the period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

1

Motorists Injured

Prior: 3-66.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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 year-over-year. In June 2025, the peak day for crashes was Saturday with 3 incidents, differing from June 2024 where Thursday saw the highest count with 8 crashes. The peak crash hour also changed from 9 p.m. with 4 crashes in June 2024 to 4 p.m. with 3 crashes in June 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either June 2024 or June 2025. Total injuries decreased substantially from 6 in June 2024 to 1 in June 2025. The proportion of crashes resulting in minor injury slightly decreased from 9.1% of crashes in the prior period to 7.7% in the current period, with no possible injuries reported in the current period.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes7.7%
-66.7%prior 3
No Injury12no injury crashes92.3%
-55.6%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'No improper driving' decreased from 9 in June 2024 to 4 in June 2025, a reduction of 5 crashes. 'Failed to yield right of way' incidents decreased by 1 crash, from 4 to 3, while 'Inattention' crashes also saw a decrease of 2, from 4 to 2. Factors such as 'Visibility obstructed' and 'Fatigued/asleep', which accounted for 2 crashes each in the prior period, were not reported in the current period.

Officer-Reported Primary Contributing Cause

No improper driving4 (30.8%)-55.6%prior 9
Failed to yield right of way3 (23.1%)
Inattention2 (15.4%)
Followed too closely1 (7.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (7.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The number of crashes under clear weather conditions decreased from 29 in June 2024 to 8 in June 2025. While the absolute number of crashes on wet road surfaces remained at 2 in both periods, their share of total crashes increased from 6.1% in June 2024 to 15.4% in June 2025. Crashes occurring during non-daylight conditions decreased from 7 in June 2024 to 2 in June 2025, with their share of total crashes falling from 21.2% to 15.4%.

Weather

Clear8 (61.5%)
-72.4%prior 29
Clear/Clear2 (15.4%)
Cloudy2 (15.4%)
Clear/Cloudy1 (7.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Weather condition at time of crash

Lighting

Daylight11 (84.6%)
-57.7%prior 26
Dark - lighted roadway1 (7.7%)
Dusk1 (7.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Lighting condition field

Road Surface

Dry11 (84.6%)
-64.5%prior 31
Wet2 (15.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (21 vehicles)

1
TOYOTA5 (23.8%)
-37.5%prior 8
2
NISSAN4 (19%)
3
GMC3 (14.3%)
4
HONDA3 (14.3%)
-57.1%prior 7
5
JEEP1 (4.8%)
6
ACURA1 (4.8%)
7
VOLKSWAGEN1 (4.8%)
8
CHEVROLET1 (4.8%)
9
DODGE1 (4.8%)
10
FORD1 (4.8%)
-88.9%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Vehicle unit records

Sex Distribution (30 persons with recorded sex)

Male17 (56.7%)
-62.2%prior 45
Female13 (43.3%)
-48.0%prior 25

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone decreased from 9 in June 2024 to 3 in June 2025, a reduction of 6 crashes. Similarly, the 40 mph zone saw a decrease of 3 crashes, from 9 to 6, and the 65 mph zone also decreased by 3 crashes, from 5 to 2. Notably, speed zones such as 10 mph, 35 mph, and 45 mph, which collectively accounted for 9 crashes in the prior period, had no reported crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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: 2025-06-01 through 2025-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-06-01 through 2025-06-30 (30 days)
  • Geographic scope: NORTON, MA
  • Total crash records analyzed: 13
  • Total persons involved: 30
  • Total vehicles involved: 21

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). "NORTON, MA Crash Intelligence Report: June 2025." Published June 21, 2026. Reporting period: 2025-06-01 to 2025-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/norton/june-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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Norton, MA Crash Report — June 2025 | ThatCarHitMe.com