Monthly Traffic Safety Analysis

26 CRASHES IN
NORWOOD, MA
NOVEMBER 2025

All metrics benchmarked againstNovember 2024

In November 2025, Norwood experienced 26 crashes, a 33.33% decrease from the 39 crashes recorded in November 2024. Despite the overall reduction in incidents, the number of fatalities remained constant at 1 in both periods. The most notable shift was a significant drop in crashes attributed to 'No improper driving', decreasing from 13 to 5 incidents.

26

▼ -33.3%was 39

Total Crash Events

1

Persons Killed

10

▲ 25.0%was 8

Persons Injured

1

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 Norwood decreased significantly year-over-year, falling by 33.33% from 39 incidents in November 2024 to 26 in November 2025. While total crashes declined, the number of fatalities remained stable at 1 in both periods, and total injuries increased by 25% from 8 to 10.

1

Hit-and-Run Crashes — November 2025

▼ 0.0% vs prior (1)

The number of hit-and-run crashes remained stable at 1 in both November 2024 and November 2025. However, due to a decrease in overall crashes, the hit-and-run rate increased from 2.6% to 3.8% year-over-year.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0→%

10

Motorists Injured

Prior: 6↑66.7%

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 temporal patterns for crashes shifted between the two periods. In November 2025, Monday became the peak day with 6 crashes, replacing Wednesday which had 8 crashes in November 2024. The peak hour also moved from 5 PM with 7 crashes in November 2024 to 11 AM with 4 crashes in November 2025.

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

The total number of fatalities remained constant at 1 in both November 2024 and November 2025, although the fatal crash rate increased from 2.56% to 3.85% due to fewer overall crashes. Total injuries rose by 25%, from 8 in November 2024 to 10 in November 2025. Minor injury crashes decreased from 6 to 5, while possible injury crashes remained stable at 2.

Outcome by Severity (Crash Events)

Fatal1fatal crashes3.8%
→0.0%prior 1
Minor Injury5minor injury crashes19.2%
↓-16.7%prior 6
Possible Injury2possible injury crashes7.7%
No Injury18no injury crashes69.2%
↓-43.8%prior 32

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

Analysis of contributing factors reveals significant shifts year-over-year. Crashes attributed to 'No improper driving' saw the largest decrease, falling by 8 incidents from 13 in November 2024 to 5 in November 2025, a 61.5% reduction. Conversely, 'Followed too closely' incidents increased by 4, from 2 to 6, representing a 200% rise. 'Failed to yield right of way' decreased by 2 crashes (40%) and 'Inattention' decreased by 1 crash (25%).

Officer-Reported Primary Contributing Cause

Followed too closely6 (23.1%)
No improper driving5 (19.2%)↓-61.5%prior 13
Inattention3 (11.5%)
Failed to yield right of way3 (11.5%)↓-40.0%prior 5
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (7.7%)
Made an improper turn1 (3.8%)
Other improper action1 (3.8%)
Over-correcting/over-steering1 (3.8%)

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

Clear weather conditions were associated with 14 crashes in November 2025, a decrease from 31 in November 2024, while crashes in rainy conditions decreased from 3 to 2. In terms of lighting, crashes occurring in 'Dark - lighted roadway' conditions decreased substantially from 14 to 4. Dry road surface crashes also saw a reduction from 29 to 23, and wet road surface crashes decreased from 6 to 3.

Weather

Clear14 (53.8%)
↓-54.8%prior 31
Clear/Clear3 (11.5%)
Rain2 (7.7%)
Clear/Unknown2 (7.7%)
Cloudy2 (7.7%)
Clear/Cloudy1 (3.8%)
Clear/Other1 (3.8%)
Cloudy/Cloudy1 (3.8%)

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

Lighting

Daylight18 (69.2%)
↓-10.0%prior 20
Dark - lighted roadway4 (15.4%)
↓-71.4%prior 14
Dark - roadway not lighted2 (7.7%)
Dusk2 (7.7%)

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

Road Surface

Dry23 (88.5%)
↓-20.7%prior 29
Wet3 (11.5%)
↓-50.0%prior 6

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 (47 vehicles)

1
TOYOTA10 (21.3%)
↓-28.6%prior 14
2
FORD8 (17%)
↓-50.0%prior 16
3
HONDA4 (8.5%)
↓-50.0%prior 8
4
HYUNDAI4 (8.5%)
5
NISSAN3 (6.4%)
6
LEXUS2 (4.3%)
7
KIA2 (4.3%)
8
MAZDA2 (4.3%)
9
SUBARU2 (4.3%)
10
DODGE2 (4.3%)

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

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

Sex Distribution (55 persons with recorded sex)

Male28 (50.9%)
↓-34.9%prior 43
Female27 (49.1%)
↓-35.7%prior 42

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 30 mph zones significantly decreased from 29 in November 2024 to 10 in November 2025, but this zone recorded 1 fatality in the current period compared to none previously. Conversely, the 25 mph zone had 1 crash in both periods, but the fatal crash occurred in the prior period. Crashes in 45 mph zones slightly increased from 3 to 4.

Fatal crashes by zone: 30 mph: 1 of 10 (10%)

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: NORWOOD, MA
  • Total crash records analyzed: 26
  • Total persons involved: 57
  • Total vehicles involved: 47

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). "NORWOOD, 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/norwood/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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Norwood, MA Crash Report — November 2025 | ThatCarHitMe.com