ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEWTON, 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/newton/march-2026-report
Monthly Traffic Safety Analysis
138 CRASHES IN
NEWTON, MA
MARCH 2026
In March 2026, the city of NEWTON experienced 138 total crashes, an increase from the 113 crashes recorded in March 2025. This represents a 22.12% rise in overall crash incidents year-over-year. A notable positive shift was the absence of traffic fatalities in March 2026, compared to one fatality in March 2025.
138
▲ 22.1%was 113
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
16
▲ 6.7%was 15
Persons Injured
16
▲ 6.7%was 15
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. 7 crashes with unreported severity are not shown in the severity breakdown.
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 indicates a rise in crash incidents, with total crashes increasing from 113 in March 2025 to 138 in March 2026. This constitutes a 22.12% increase in crashes year-over-year. Despite the increase in total crashes, the number of persons injured remained relatively stable, rising slightly from 15 to 16.
16
Hit-and-Run Crashes — March 2026
▲ 6.7% vs prior (15)
The number of hit-and-run crashes increased slightly from 15 in March 2025 to 16 in March 2026. Despite this increase in count, the hit-and-run rate relative to total crashes decreased from 13.3% in the prior period to 11.6% in the current period.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
15
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 peak day for crashes shifted from Friday in March 2025, which saw 23 incidents, to Tuesday in March 2026, with 35 incidents. The peak hour for crashes also changed, moving from 5 PM (10 crashes) in the prior period to 8 AM (16 crashes) in the current period. This indicates a shift in high-crash periods from late afternoon to morning commute times.
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
Fatal crashes decreased from 1 in March 2025 to 0 in March 2026, resulting in no fatalities in the current period compared to 1 fatality previously. Serious injuries (Severity A) decreased from 2 (1.8% of crashes) to 1 (0.7% of crashes) year-over-year. Minor injuries (Severity B) also saw a reduction, from 12 (10.6% of crashes) to 9 (6.5% of crashes).
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
Inattention remained the most frequently cited contributing factor, with 33 crashes in both periods. Crashes attributed to 'No improper driving' significantly increased from 12 to 22, an 83.3% rise in count. Conversely, crashes where 'Followed too closely' was a factor decreased from 19 to 14, a 26.3% reduction in count. 'Driving too fast for conditions' was noted in 7 crashes in the current period but was not a listed factor in the prior period, while 'Exceeded authorized speed limit' was a factor in 2 crashes in the prior period but not listed in the current 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
Crashes occurring in 'Clear' weather conditions increased from 67 to 72 year-over-year. Incidents on 'Wet' road surfaces rose from 19 to 32, representing a 68.4% increase. Crashes during 'Daylight' conditions also increased, from 89 to 99.
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 increased from 219 in March 2025 to 263 in March 2026. The 65+ age group saw a substantial increase in persons involved, rising from 27 to 49. Toyota continued to be the most frequently involved vehicle make, with its count increasing from 34 to 43 vehicles.
Top Vehicle Makes (263 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Vehicle unit records
31 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (280 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 occurring in 25 mph speed zones increased from 50 in March 2025 to 75 in March 2026. Conversely, crashes in 55 mph zones saw a slight decrease, from 16 to 14 incidents. The prior period recorded 1 fatal crash in a 40 mph zone, whereas the current period reported no fatal crashes across any speed limit.
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: NEWTON, MA
- Total crash records analyzed: 138
- Total persons involved: 313
- Total vehicles involved: 263
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). "NEWTON, 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/newton/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