Monthly Traffic Safety Analysis

29 CRASHES IN
NORWOOD, MA
SEPTEMBER 2025

All metrics benchmarked againstSeptember 2024

NORWOOD experienced 29 crashes in September 2025, a 14.7% decrease compared to the 34 crashes recorded in September 2024. Despite the reduction in overall crashes, total injuries increased by 23.1%, rising from 13 injured persons in the prior period to 16 in the current period. Fatalities remained at zero for both periods.

29

-14.7%was 34

Total Crash Events

0

Persons Killed

16

23.1%was 13

Persons Injured

1

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 · 2025-09-01 to 2025-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash incidents in NORWOOD decreased year-over-year, with a 14.7% reduction from 34 crashes in September 2024 to 29 crashes in September 2025. However, the number of injured persons increased by 23.1%, from 13 to 16, indicating a rise in injury severity despite fewer total crashes.

1

Hit-and-Run Crashes — September 2025

3.4% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

16

Motorists Injured

Prior: 1145.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year, with the peak day moving from Tuesday in September 2024 to Thursday in September 2025, both recording 6 crashes. The peak hour also changed, moving from 12p with 6 crashes in the prior period to 8a with 4 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero in both September 2024 and September 2025. While total injuries increased from 13 to 16, the distribution of injury severity changed: serious injuries (severity A) decreased from 1 crash (2.9% share) to 0, while minor injuries (severity B) increased from 4 crashes (11.8% share) to 11 crashes (37.9% share). Possible injuries (severity C) decreased from 4 crashes (11.8% share) to 2 crashes (6.9% share), and crashes with no injury decreased from 25 (73.5% share) to 16 (55.2% share).

Outcome by Severity (Crash Events)

Minor Injury11minor injury crashes37.9%
175.0%prior 4
Possible Injury2possible injury crashes6.9%
-50.0%prior 4
No Injury16no injury crashes55.2%
-36.0%prior 25

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors saw shifts in counts and rankings. 'No improper driving' increased by 3 crashes, from 5 in September 2024 to 8 in September 2025, becoming the most frequent factor. Conversely, 'Inattention' and 'Failed to yield right of way' each decreased by 2 crashes, from 6 to 4, representing a 33.3% decrease in count for both. 'Distracted' driving crashes doubled, increasing from 1 to 2 incidents.

Officer-Reported Primary Contributing Cause

No improper driving8 (27.6%)60.0%prior 5
Inattention4 (13.8%)-33.3%prior 6
Failed to yield right of way4 (13.8%)-33.3%prior 6
Other improper action2 (6.9%)
Distracted2 (6.9%)
Disregarded traffic signs, signals, road markings2 (6.9%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (3.4%)
Driving too fast for conditions1 (3.4%)
Failure to keep in proper lane or running off road1 (3.4%)
Followed too closely1 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a notable shift towards crashes occurring in adverse conditions. Crashes in 'Clear' weather decreased from 26 to 18, while those in 'Rain' increased from 1 to 4. Similarly, 'Dry' road surface crashes decreased from 29 to 23, but 'Wet' road surface crashes increased from 4 to 6. Crashes occurring in 'Daylight' decreased from 28 to 23, while those in 'Dark - lighted roadway' increased from 5 to 6.

Weather

Clear18 (62.1%)
-30.8%prior 26
Rain4 (13.8%)
Clear/Unknown2 (6.9%)
Cloudy/Clear1 (3.4%)
Cloudy/Rain1 (3.4%)
Rain/Rain1 (3.4%)
Clear/Clear1 (3.4%)
Cloudy1 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Weather condition at time of crash

Lighting

Daylight23 (79.3%)
-17.9%prior 28
Dark - lighted roadway6 (20.7%)
20.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Lighting condition field

Road Surface

Dry23 (79.3%)
-20.7%prior 29
Wet6 (20.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Road surface condition field

Vehicles & Demographics

Vehicle involvement saw shifts in top makes, with Toyota crashes decreasing from 15 to 7, while Ford crashes increased from 7 to 9. The demographic profile of persons involved in crashes also changed significantly. There was a notable decrease in involvement for younger age groups, with persons aged 0-15 dropping from 9 to 2, and 16-20 dropping from 10 to 3. Conversely, persons aged 21-25 increased from 5 to 7, and those 65 and older increased from 11 to 12.

Top Vehicle Makes (61 vehicles)

1
FORD9 (14.8%)
28.6%prior 7
2
TOYOTA7 (11.5%)
-53.3%prior 15
3
HONDA5 (8.2%)
-16.7%prior 6
4
CHEVROLET5 (8.2%)
0.0%prior 5
5
HYUNDAI4 (6.6%)
6
NISSAN3 (4.9%)
7
ACURA2 (3.3%)
8
AUDI2 (3.3%)
9
BMW2 (3.3%)
10
JEEP2 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Vehicle unit records

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

Sex Distribution (62 persons with recorded sex)

Male35 (56.5%)
-22.2%prior 45
Female27 (43.5%)
-22.9%prior 35

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone decreased from 24 in September 2024 to 19 in September 2025. Crashes in the 45 mph zone also saw a slight decrease from 3 to 2, and 50 mph crashes decreased from 2 to 1. Notably, the current period introduced crashes in 15 mph (1 crash), 35 mph (2 crashes), and 65 mph (2 crashes) zones, which were not present in the prior period, while crashes in 25 mph zones (4 crashes) were no longer recorded. No fatalities were reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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: 2025-09-01 through 2025-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-09-01 through 2025-09-30 (30 days)
  • Geographic scope: NORWOOD, MA
  • Total crash records analyzed: 29
  • Total persons involved: 74
  • Total vehicles involved: 61

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: September 2025." Published June 21, 2026. Reporting period: 2025-09-01 to 2025-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/norwood/september-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 — September 2025 | ThatCarHitMe.com