ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEWTON, MA · FEBRUARY 2025
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/february-2025-report
Monthly Traffic Safety Analysis
132 CRASHES IN
NEWTON, MA
FEBRUARY 2025
Total crashes in Newton, MA increased by 20% from 110 in February 2024 to 132 in February 2025. While total fatalities remained at zero, total injuries rose by 41.18% from 17 to 24. The most significant year-over-year shift was a 700% increase in speeding crashes, from 1 in February 2024 to 8 in February 2025.
132
▲ 20.0%was 110
Total Crash Events
0
Persons Killed
24
▲ 41.2%was 17
Persons Injured
14
▼ -30.0%was 20
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. 4 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for Newton, MA indicates an upward trend in February 2025 compared to February 2024. Total crashes increased by 20%, rising from 110 to 132. Concurrently, total injuries saw a substantial 41.18% increase, from 17 to 24, while fatalities remained at zero in both periods.
14
Hit-and-Run Crashes — February 2025
▼ -30.0% vs prior (20)
The number of hit-and-run crashes decreased by 6 incidents, from 20 in February 2024 to 14 in February 2025. Consequently, the hit-and-run rate declined from 18.2% of all crashes in February 2024 to 10.6% in February 2025. This indicates a downward trend in hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
0
Other Killed
1
Pedestrians Injured
22
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes shifted year-over-year. In February 2024, the peak day for crashes was Thursday with 25 incidents, and the peak hour was 4 PM with 12 crashes. In February 2025, the peak day shifted to Sunday with 23 crashes, and the peak hour became 7 AM with 16 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The overall injury landscape saw an increase in February 2025, with total injuries rising from 17 to 24. Serious injuries (Severity A) decreased from 2 crashes (1.8% share) in February 2024 to 1 crash (0.8% share) in February 2025. Conversely, minor injuries (Severity B) increased from 8 crashes (7.3% share) to 16 crashes (12.1% share) during the same period.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Most severe injury per crash record
Top Contributing Factors
Inattention became the leading contributing factor in February 2025, increasing by 11 crashes from 19 to 30, while No improper driving decreased by 6 crashes from 29 to 23. Factors such as Followed too closely and Failed to yield right of way both increased by 3 crashes, rising from 10 to 13 each. Notably, Driving too fast for conditions crashes increased significantly from 1 in February 2024 to 5 in February 2025, representing a 400% rise in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Adverse weather and road surface conditions were more prevalent in February 2025 compared to the prior year. Crashes occurring in snow, sleet, or rain conditions increased from 7 in February 2024 to 37 in February 2025. Similarly, crashes on wet, snowy, icy, or slushy road surfaces rose from 8 in February 2024 to 42 in February 2025. Daylight remained the dominant lighting condition for crashes in both periods, with 79 incidents in February 2024 and 78 in February 2025.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 206 in February 2024 to 250 in February 2025. Toyota remained the most frequently involved make, increasing from 41 to 47 vehicles, while Honda also saw an increase from 19 to 32 vehicles. The age distribution of persons involved showed a notable decrease in the 0-15 age group, from 38 to 7, and an increase in the 26-34 age group, from 37 to 58.
Top Vehicle Makes (250 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Vehicle unit records
31 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (279 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Person-level records linked to crash events
Speed Limit Zones
Crashes increased across several common speed limit zones year-over-year. Incidents in 25 mph zones rose from 58 to 67, and in 30 mph zones from 15 to 22. Crashes in 55 mph zones also increased from 13 to 17. No fatal crashes were recorded in any speed limit zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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: 2025-02-01 through 2025-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-02-01 through 2025-02-28 (28 days)
- Geographic scope: NEWTON, MA
- Total crash records analyzed: 132
- Total persons involved: 308
- Total vehicles involved: 250
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: February 2025." Published June 21, 2026. Reporting period: 2025-02-01 to 2025-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/newton/february-2025-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: 2025-02-01 – 2025-02-28
Generated: June 21, 2026 · All rights reserved