Yearly Traffic Safety Analysis

409 CRASHES IN
NORWOOD, MA
2025

All metrics benchmarked against2024

In 2025, NORWOOD recorded 409 total crashes, a 1.2% decrease from the 414 crashes reported in 2024. While overall collisions remained stable, the most significant year-over-year change was in crash outcomes. The number of total fatalities decreased from 3 in 2024 to 1 in 2025.

409

-1.2%was 414

Total Crash Events

1

-66.7%was 3

Persons Killed

162

15.7%was 140

Persons Injured

13

62.5%was 8

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. 2 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume in NORWOOD remained relatively stable, decreasing by 1.2% from 414 incidents in 2024 to 409 in 2025. However, the number of people injured in these crashes increased by 15.7%, rising from 140 in the prior year to 162 in the current year. This indicates that while total crashes slightly declined, the incidents that did occur resulted in more injuries.

13

Hit-and-Run Crashes — 2025

62.5% vs prior (8)

Hit-and-run incidents showed a significant upward trend year-over-year. The number of hit-and-run crashes increased by 62.5%, from 8 incidents in 2024 to 13 in 2025. Consequently, the hit-and-run rate, representing the percentage of total crashes that were hit-and-runs, rose from 1.9% to 3.2%.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 2-50.0%

3

Pedestrians Injured

Prior: 9-66.7%

1

Cyclists Injured

Prior: 10.0%

158

Motorists Injured

Prior: 12922.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts year-over-year. In 2025, the peak day for crashes moved to Friday with 68 incidents, compared to Wednesday (77 incidents) in 2024. Similarly, the peak hour for collisions shifted from 1 PM in the prior year (40 crashes) to 2 PM in the current year (35 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity saw a notable improvement, with fatal crashes decreasing from 3 in 2024 to 1 in 2025, causing the fatal crash rate to fall from 0.72% to 0.24%. The proportion of crashes resulting in any injury remained nearly constant, moving from 26.3% to 26.9%. Within injury crashes, the share of minor injury crashes increased from 14.3% to 17.1% of all incidents, while the share of serious and possible injury crashes saw small decreases.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.2%
-66.7%prior 3
Serious Injury8serious injury crashes2%
-11.1%prior 9
Minor Injury70minor injury crashes17.1%
18.6%prior 59
Possible Injury31possible injury crashes7.6%
-18.4%prior 38
No Injury297no injury crashes72.6%
-1.7%prior 302

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

The primary contributing factors cited in crashes remained consistent year-over-year, with the top four reasons maintaining their rank. 'Failed to yield right of way' incidents decreased in count from 59 to 55, and 'Inattention' dropped from 52 to 48 cases. Conversely, crashes attributed to 'Distracted' driving, while a smaller category, saw a 22.2% increase in count, rising from 9 incidents in 2024 to 11 in 2025.

Officer-Reported Primary Contributing Cause

No improper driving108 (26.4%)-1.8%prior 110
Failed to yield right of way55 (13.4%)-6.8%prior 59
Inattention48 (11.7%)-7.7%prior 52
Followed too closely39 (9.5%)2.6%prior 38
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner21 (5.1%)10.5%prior 19
Failure to keep in proper lane or running off road18 (4.4%)28.6%prior 14
Disregarded traffic signs, signals, road markings16 (3.9%)0.0%prior 16
Other improper action15 (3.7%)15.4%prior 13
Distracted11 (2.7%)22.2%prior 9
Made an improper turn8 (2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The conditions under which crashes occurred shifted between the two periods. In 2025, a larger proportion of crashes happened on dry roads (83.6%) compared to 2024 (73.7%), with a corresponding decrease in the share of crashes on wet surfaces from 20.0% to 13.0%. While the majority of crashes in both years occurred in daylight, there was a notable drop in collisions on dark, lighted roadways, which fell from 80 incidents in 2024 to 61 in 2025.

Weather

Clear264 (64.5%)
-2.9%prior 272
Clear/Clear27 (6.6%)
Rain25 (6.1%)
-10.7%prior 28
Cloudy24 (5.9%)
-27.3%prior 33
Clear/Unknown18 (4.4%)
28.6%prior 14
Clear/Other12 (2.9%)
71.4%prior 7
Cloudy/Rain7 (1.7%)
-61.1%prior 18
Snow6 (1.5%)
-57.1%prior 14
Rain/Cloudy4 (1.0%)
-33.3%prior 6
Clear/Cloudy4 (1.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight307 (75.1%)
0.3%prior 306
Dark - lighted roadway61 (14.9%)
-23.8%prior 80
Dark - roadway not lighted15 (3.7%)
7.1%prior 14
Dusk14 (3.4%)
100.0%prior 7
Dawn10 (2.4%)
42.9%prior 7
Dark - unknown roadway lighting1 (0.2%)
Other1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry342 (83.6%)
12.1%prior 305
Wet53 (13.0%)
-36.1%prior 83
Snow14 (3.4%)
0.0%prior 14

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

Analysis of involved vehicles and persons reveals shifts in both categories. While Toyota remained the most frequently involved vehicle make in both years, Honda's involvement saw a significant decrease from 121 vehicles in 2024 to 81 in 2025, dropping it from the second to the third-ranked make behind Ford. Demographically, there was a notable increase in crash participants from older age groups; the 55-64 age group grew from 108 to 131 individuals, and the 65+ group increased from 126 to 154 individuals.

Top Vehicle Makes (793 vehicles)

1
TOYOTA146 (18.4%)
-2.0%prior 149
2
FORD92 (11.6%)
5.7%prior 87
3
HONDA81 (10.2%)
-33.1%prior 121
4
NISSAN51 (6.4%)
64.5%prior 31
5
CHEVROLET50 (6.3%)
8.7%prior 46
6
JEEP43 (5.4%)
34.4%prior 32
7
SUBARU30 (3.8%)
50.0%prior 20
8
KIA27 (3.4%)
17.4%prior 23
9
HYUNDAI26 (3.3%)
30.0%prior 20
10
MAZDA23 (2.9%)
43.8%prior 16

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (941 persons with recorded sex)

Male512 (54.4%)
-4.8%prior 538
Female429 (45.6%)
10.6%prior 388

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

The 30 mph speed zone remained the location for the highest number of crashes in both years, although the count decreased from 244 in 2024 to 222 in 2025. The single fatal crash in 2025 occurred in a 30 mph zone, down from two fatalities in that zone the previous year. A notable shift occurred in higher speed zones, with crashes in 65 mph zones increasing by 56%, from 25 incidents in 2024 to 39 in 2025.

Fatal crashes by zone: 30 mph: 1 of 222 (0.45%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: NORWOOD, MA
  • Total crash records analyzed: 409
  • Total persons involved: 1,004
  • Total vehicles involved: 793

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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/norwood/2025-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 — 2025 | ThatCarHitMe.com