Yearly Traffic Safety Analysis

375 CRASHES IN
NORWOOD, MA
2023

All metrics benchmarked against2022

In 2023, Norwood recorded 375 total traffic crashes, representing a 3.9% increase from the 361 crashes documented in 2022. The most significant year-over-year change was the occurrence of one fatal crash in 2023, whereas there were no fatal crashes in the prior year. Overall injuries also rose from 134 to 141.

375

3.9%was 361

Total Crash Events

1

Persons Killed

141

5.2%was 134

Persons Injured

5

25.0%was 4

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash totals in Norwood experienced a modest increase year-over-year. In 2023, there were 375 crashes, up 3.9% from 361 in 2022. The number of people injured also rose by 5.2% during the same period, increasing from 134 to 141.

5

Hit-and-Run Crashes — 2023

25.0% vs prior (4)

The number of hit-and-run incidents in Norwood saw a slight increase between 2022 and 2023. The total count of hit-and-run crashes rose from 4 to 5. This resulted in the hit-and-run rate increasing from 1.1% of all crashes in 2022 to 1.3% in 2023.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

2

Pedestrians Injured

Prior: 8-75.0%

3

Cyclists Injured

Prior: 4-25.0%

136

Motorists Injured

Prior: 12211.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes in Norwood shifted between the two years. In 2023, the peak day for crashes was Thursday with 62 incidents, a change from 2022 when Wednesday and Friday were the peak days with 64 crashes each. The busiest hour for crashes also moved earlier in the day, from 3 p.m. in 2022 (31 crashes) to 1 p.m. in 2023 (30 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

In 2023, Norwood recorded one fatal crash, compared to zero in 2022. Despite this, the number of crashes resulting in serious injuries decreased by 50%, from 10 incidents in 2022 to 5 in 2023. The share of crashes involving minor injuries increased slightly from 17.2% to 18.4% of all crashes, while the proportion of non-injury crashes remained stable at approximately 72% for both years.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.3%
Serious Injury5serious injury crashes1.3%
-50.0%prior 10
Minor Injury69minor injury crashes18.4%
11.3%prior 62
Possible Injury28possible injury crashes7.5%
3.7%prior 27
No Injury271no injury crashes72.3%
4.2%prior 260

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors to crashes showed notable shifts between periods. Crashes attributed to 'Failed to yield right of way' increased by 65.9% in count, rising from 41 incidents in 2022 to 68 in 2023, and moving from the fourth to the second-ranked cause. 'Inattention' also saw a 21.4% increase in count, from 42 to 51 crashes. Conversely, crashes involving 'Followed too closely' decreased by 10.2%, from 49 to 44 incidents.

Officer-Reported Primary Contributing Cause

No improper driving71 (18.9%)-16.5%prior 85
Failed to yield right of way68 (18.1%)65.9%prior 41
Inattention51 (13.6%)21.4%prior 42
Followed too closely44 (11.7%)-10.2%prior 49
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner25 (6.7%)8.7%prior 23
Failure to keep in proper lane or running off road16 (4.3%)14.3%prior 14
Disregarded traffic signs, signals, road markings14 (3.7%)-12.5%prior 16
Other improper action12 (3.2%)50.0%prior 8
Distracted11 (2.9%)22.2%prior 9
Made an improper turn9 (2.4%)80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring on wet roads saw a notable increase, rising from 61 incidents in 2022 to 82 in 2023, a 34.4% jump in count. This corresponds with an increase in crashes reported during rainy weather, which went from 24 to 37. While the majority of crashes in both years occurred on dry roads, the share of crashes on wet surfaces grew from 16.9% of total crashes in 2022 to 21.9% in 2023.

Weather

Clear251 (67.1%)
-6.3%prior 268
Rain37 (9.9%)
54.2%prior 24
Cloudy30 (8.0%)
30.4%prior 23
Clear/Unknown13 (3.5%)
0.0%prior 13
Cloudy/Rain10 (2.7%)
Clear/Other7 (1.9%)
Rain/Cloudy5 (1.3%)
Rain/Snow3 (0.8%)
Snow2 (0.5%)
-71.4%prior 7
Rain/Unknown2 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight263 (70.3%)
1.5%prior 259
Dark - lighted roadway74 (19.8%)
13.8%prior 65
Dark - roadway not lighted16 (4.3%)
-23.8%prior 21
Dusk10 (2.7%)
0.0%prior 10
Dawn9 (2.4%)
Dark - unknown roadway lighting2 (0.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry286 (76.5%)
-0.7%prior 288
Wet82 (21.9%)
34.4%prior 61
Sand, mud, dirt, oil, gravel2 (0.5%)
Ice2 (0.5%)
Slush1 (0.3%)
Snow1 (0.3%)
-83.3%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

While the top three vehicle makes involved in crashes—Toyota, Honda, and Ford—remained consistent across both years, there were notable shifts in the age demographics of people involved. The number of individuals aged 0-15 involved in crashes increased by 63.6%, from 44 to 72. Similarly, involvement for the 21-25 age group rose by 30% (from 70 to 91 people) and the 65+ group by 25.7% (from 101 to 127 people). Conversely, the 26-34 age group saw a 14.1% decrease in persons involved.

Top Vehicle Makes (698 vehicles)

1
TOYOTA133 (19.1%)
10.8%prior 120
2
HONDA86 (12.3%)
-2.3%prior 88
3
FORD75 (10.7%)
-7.4%prior 81
4
CHEVROLET50 (7.2%)
13.6%prior 44
5
NISSAN37 (5.3%)
5.7%prior 35
6
SUBARU28 (4%)
115.4%prior 13
7
JEEP27 (3.9%)
-10.0%prior 30
8
BMW24 (3.4%)
41.2%prior 17
9
GMC22 (3.2%)
69.2%prior 13
10
HYUNDAI21 (3%)
-25.0%prior 28

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (847 persons with recorded sex)

Male514 (60.7%)
9.6%prior 469
Female333 (39.3%)
-1.5%prior 338

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones changed year-over-year, with a notable shift in concentration. Crashes in 30 mph zones increased by 17.2%, from 203 in 2022 to 238 in 2023. In contrast, crashes in 65 mph zones saw a 38.9% decrease, falling from 36 to 22 incidents. The single fatal crash recorded in 2023 occurred in a 20 mph zone.

Fatal crashes by zone: 20 mph: 1 of 8 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: NORWOOD, MA
  • Total crash records analyzed: 375
  • Total persons involved: 894
  • Total vehicles involved: 698

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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/norwood/2023-annual-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 — 2023 | ThatCarHitMe.com