Monthly Traffic Safety Analysis

20 CRASHES IN
NORWOOD, MA
JANUARY 2023

All metrics benchmarked againstJanuary 2022

In January 2023, Norwood experienced 20 total crashes, a notable decrease of 42.86% compared to the 35 crashes recorded in January 2022. Total injuries also saw a significant reduction, falling from 12 in the prior year to 5 in the current period, representing a 58.33% decrease. The most notable year-over-year shift was the substantial decline in overall crash and injury numbers.

20

-42.9%was 35

Total Crash Events

0

Persons Killed

5

-58.3%was 12

Persons Injured

0

Fatal Crash Events

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 · 2023-01-01 to 2023-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash data for Norwood indicates a significant downward trend year-over-year, with total crashes decreasing by 42.86% from 35 in January 2022 to 20 in January 2023. Similarly, total injuries fell by 58.33%, from 12 to 5, indicating a positive trend in traffic safety outcomes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

5

Motorists Injured

Prior: 11-54.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · 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 between the two periods. The peak day for crashes moved from Friday with 8 crashes in January 2022 to Tuesday with 6 crashes in January 2023. The peak hour also changed, shifting from 2 PM with 6 crashes in the prior period to 5 PM with 3 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

No fatal crashes were reported in either January 2022 or January 2023. The total number of injuries decreased from 12 in the prior period to 5 in the current period. In January 2022, there were 2 serious injuries and 7 minor injuries, while in January 2023, there were 3 minor injuries, indicating a reduction in the severity of reported injuries.

Outcome by Severity (Crash Events)

Minor Injury3minor injury crashes15%
-57.1%prior 7
No Injury17no injury crashes85%
-32.0%prior 25

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors shifted year-over-year. 'Failed to yield right of way' increased from 4 crashes in January 2022 to 5 crashes in January 2023, making it the top factor in the current period. Conversely, 'No improper driving' decreased from 8 crashes to 3 crashes, and 'Inattention' decreased from 4 crashes to 1 crash.

Officer-Reported Primary Contributing Cause

Failed to yield right of way5 (25%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (15%)
No improper driving3 (15%)-62.5%prior 8
Followed too closely2 (10%)
Over-correcting/over-steering1 (5%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (5%)
Disregarded traffic signs, signals, road markings1 (5%)
Driving too fast for conditions1 (5%)
Failure to keep in proper lane or running off road1 (5%)
Inattention1 (5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a notable shift in the conditions under which crashes occurred. Crashes during clear weather conditions decreased from 26 in January 2022 to 7 in January 2023, while crashes on wet road surfaces increased from 6 to 12. Additionally, crashes occurring in daylight decreased from 23 to 8, with crashes in 'Dark - lighted roadway' increasing from 6 to 9.

Weather

Clear7 (35.0%)
-73.1%prior 26
Rain6 (30.0%)
Cloudy2 (10.0%)
Rain/Snow2 (10.0%)
Clear/Unknown1 (5.0%)
Rain/Unknown1 (5.0%)
Snow1 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Weather condition at time of crash

Lighting

Dark - lighted roadway9 (45.0%)
50.0%prior 6
Daylight8 (40.0%)
-65.2%prior 23
Dark - roadway not lighted2 (10.0%)
Dusk1 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Lighting condition field

Road Surface

Wet12 (60.0%)
100.0%prior 6
Dry7 (35.0%)
-69.6%prior 23
Slush1 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (37 vehicles)

1
HONDA5 (13.5%)
-28.6%prior 7
2
CHEVROLET4 (10.8%)
-42.9%prior 7
3
FORD4 (10.8%)
-42.9%prior 7
4
TOYOTA3 (8.1%)
-62.5%prior 8
5
VOLVO2 (5.4%)
6
BMW2 (5.4%)
7
MAZDA2 (5.4%)
8
NISSAN2 (5.4%)
9
HYUNDAI2 (5.4%)
10
SUBARU1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Vehicle unit records

Sex Distribution (46 persons with recorded sex)

Male29 (63.0%)
-35.6%prior 45
Female17 (37.0%)
-43.3%prior 30

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed limit zone decreased from 23 in January 2022 to 16 in January 2023, remaining the most common speed zone for crashes. Crashes in the 65 mph zone also decreased from 5 to 1. There were no fatal crashes recorded in any speed limit zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · 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: 2023-01-01 through 2023-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-01-31 (31 days)
  • Geographic scope: NORWOOD, MA
  • Total crash records analyzed: 20
  • Total persons involved: 46
  • Total vehicles involved: 37

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: January 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/norwood/january-2023-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 — January 2023 | ThatCarHitMe.com