Monthly Traffic Safety Analysis

32 CRASHES IN
NORWELL, MA
NOVEMBER 2025

All metrics benchmarked againstNovember 2024

In November 2025, NORWELL experienced 32 crashes, an increase of 23.1% compared to the 26 crashes recorded in November 2024. A significant positive shift was the absence of fatalities in the current period, down from one fatality in the prior year. Additionally, DUI-related crashes increased from zero in the prior period to three in the current period.

32

23.1%was 26

Total Crash Events

0

-100.0%was 1

Persons Killed

10

11.1%was 9

Persons Injured

1

-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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in NORWELL showed an upward trend year-over-year, increasing by 6 crashes from 26 to 32. Total injuries also saw a slight increase from 9 to 10. However, a positive trend was observed in crash severity, with no fatalities reported in November 2025 compared to one fatality in November 2024.

1

Hit-and-Run Crashes — November 2025

-50.0% vs prior (2)

Hit-and-run crashes decreased from 2 incidents in November 2024 to 1 incident in November 2025. Consequently, the hit-and-run rate declined from 7.7% of total crashes to 3.1% year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1-100.0%

10

Motorists Injured

Prior: 911.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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 Sunday in November 2024 (7 crashes) to Saturday in November 2025 (7 crashes), though the count remained the same. The peak hour for crashes also changed significantly, moving from 7 AM with 4 crashes in the prior period to 7 PM with 4 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased from 1 (3.8% of total crashes) in November 2024 to 0 (0%) in November 2025. While the count of minor injuries decreased from 5 to 4, their proportion of total crashes dropped from 19.2% to 12.5%. The number of possible injuries remained stable at 2 crashes in both periods, but their share decreased from 7.7% to 6.3%.

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes12.5%
-20.0%prior 5
Possible Injury2possible injury crashes6.3%
0.0%prior 2
No Injury26no injury crashes81.3%
52.9%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'No improper driving' decreased by 4, from 13 in November 2024 to 9 in November 2025. Conversely, 'Inattention' crashes saw a significant increase, rising from 1 crash to 5 crashes year-over-year. Additionally, factors like 'Exceeded authorized speed limit' and 'Driving too fast for conditions' appeared in November 2025 with one crash each, not being present in the prior period's data.

Officer-Reported Primary Contributing Cause

No improper driving9 (28.1%)-30.8%prior 13
Inattention5 (15.6%)
Distracted2 (6.3%)
Failure to keep in proper lane or running off road2 (6.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (6.3%)
Fatigued/asleep1 (3.1%)
Exceeded authorized speed limit1 (3.1%)
Driving too fast for conditions1 (3.1%)
Physical impairment1 (3.1%)
Followed too closely1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in adverse weather conditions (Rain, Cloudy/Rain) increased from 1 crash in November 2024 to 5 crashes in November 2025, representing a rise from 3.8% to 15.6% of total crashes. Similarly, crashes on wet road surfaces increased from 2 to 7 year-over-year. Crashes occurring in darkness (Dark - lighted, Dark - not lighted, Dark - unknown) increased from 11 to 14, maintaining a similar proportion of total crashes at around 43%.

Weather

Clear21 (65.6%)
16.7%prior 18
Rain4 (12.5%)
Clear/Clear3 (9.4%)
-40.0%prior 5
Cloudy2 (6.3%)
Clear/Cloudy1 (3.1%)
Cloudy/Rain1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Weather condition at time of crash

Lighting

Daylight15 (46.9%)
25.0%prior 12
Dark - lighted roadway7 (21.9%)
Dark - roadway not lighted6 (18.8%)
-14.3%prior 7
Dusk3 (9.4%)
Dark - unknown roadway lighting1 (3.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Lighting condition field

Road Surface

Dry25 (78.1%)
4.2%prior 24
Wet7 (21.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (57 vehicles)

1
JEEP12 (21.1%)
2
TOYOTA7 (12.3%)
-22.2%prior 9
3
FORD6 (10.5%)
4
CHEVROLET5 (8.8%)
5
NISSAN4 (7%)
6
MERCEDES-BENZ3 (5.3%)
7
VOLKSWAGEN2 (3.5%)
8
GMC2 (3.5%)
9
HONDA2 (3.5%)
10
RAM2 (3.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Vehicle unit records

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

Sex Distribution (65 persons with recorded sex)

Male38 (58.5%)
26.7%prior 30
Female27 (41.5%)
42.1%prior 19

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed zone increased from 2 in November 2024 to 6 in November 2025, and those in the 40 mph zone rose from 2 to 5. There were no fatal crashes reported in any speed zone in November 2025, a decrease from the one fatal crash that occurred in a 45 mph zone in November 2024. The 45 mph speed zone, which had 2 crashes including 1 fatal crash in the prior period, is not present in the current period's data.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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: 2025-11-01 through 2025-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-11-01 through 2025-11-30 (30 days)
  • Geographic scope: NORWELL, MA
  • Total crash records analyzed: 32
  • Total persons involved: 71
  • 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). "NORWELL, MA Crash Intelligence Report: November 2025." Published June 21, 2026. Reporting period: 2025-11-01 to 2025-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/norwell/november-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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Norwell, MA Crash Report — November 2025 | ThatCarHitMe.com