ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NORWOOD, MA · MARCH 2026
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/norwood/march-2026-report
Monthly Traffic Safety Analysis
25 CRASHES IN
NORWOOD, MA
MARCH 2026
In March 2026, Norwood experienced 25 total crashes, a decrease of 21.9% compared to 32 crashes in March 2025. While total crashes decreased, the number of injured persons slightly increased from 12 to 13. A notable shift is the appearance of one serious injury crash in the current period, where there were none in the prior period.
25
▼ -21.9%was 32
Total Crash Events
0
Persons Killed
13
▲ 8.3%was 12
Persons Injured
2
▲ 100.0%was 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 · 2026-03-01 to 2026-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend for March in Norwood shows a decrease in total crashes, falling from 32 in the prior year to 25 in the current year, representing a 21.9% reduction. However, total injuries saw a slight increase of 8.3%, from 12 injured persons in March 2025 to 13 in March 2026. Fatalities remained at zero for both periods.
2
Hit-and-Run Crashes — March 2026
▲ 100.0% vs prior (1)
Hit-and-run crashes increased year-over-year, rising from 1 incident in March 2025 to 2 incidents in March 2026. This change resulted in the hit-and-run rate increasing from 3.1% of total crashes in the prior period to 8% in the current period.
Vulnerable Road User Casualties
0
Motorists Killed
13
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · 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 year-over-year, with the peak day moving from Wednesday in March 2025 (9 crashes) to Monday in March 2026 (7 crashes). The peak crash hour also changed, with March 2025 seeing its highest count at 2 PM (4 crashes) while March 2026 had its peak at 8 AM (5 crashes). Crashes on Mondays increased from 2 to 7, while crashes on Wednesdays decreased from 9 to 3.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities remained at zero for both March 2025 and March 2026. While total injuries increased from 12 to 13, the distribution of severity changed, with the current period reporting 1 serious injury crash (4% of crashes) compared to none in the prior period. Minor injury crashes remained stable at 6 in both periods, but possible injury crashes increased from 1 to 2.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Most severe injury per crash record
Top Contributing Factors
The most frequent contributing factor in March 2025, 'No improper driving' (11 crashes), decreased significantly to 3 crashes in March 2026, a 72.7% reduction in count. Conversely, 'Followed too closely' increased by 150% in count, rising from 2 crashes in the prior period to 5 crashes in the current period. 'Physical impairment' emerged as a factor in 2 crashes in the current period, having not been recorded in the prior period.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Regarding road conditions, crashes on dry surfaces decreased from 29 in March 2025 to 18 in March 2026, while crashes on wet surfaces more than doubled, increasing from 3 to 7. Daylight conditions remained the setting for 23 crashes in both periods, but crashes in 'Dark - lighted roadway' conditions decreased from 6 to 2. There was also an increase in crashes occurring during rainy weather conditions in the current period.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased by 20.6%, from 63 in March 2025 to 50 in March 2026. Toyota became the most frequently involved make in March 2026 with 9 vehicles, surpassing Honda which had 7 vehicles this year compared to 9 last year. Subaru involvement decreased from 5 vehicles in March 2025 to 1 in March 2026.
Top Vehicle Makes (50 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Vehicle unit records
5 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (58 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone decreased from 18 in March 2025 to 15 in March 2026. A notable decrease occurred in the 45 mph speed zone, which saw crashes drop from 7 to 2. Conversely, crashes in the 25 mph speed zone increased from 1 to 2, and in the 65 mph speed zone from 3 to 4.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · 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: 2026-03-01 through 2026-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2026-03-01 through 2026-03-31 (31 days)
- Geographic scope: NORWOOD, MA
- Total crash records analyzed: 25
- Total persons involved: 67
- Total vehicles involved: 50
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: March 2026." Published June 21, 2026. Reporting period: 2026-03-01 to 2026-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/norwood/march-2026-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2026-03-01 – 2026-03-31
Generated: June 21, 2026 · All rights reserved