ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEWTON, MA · JANUARY 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/january-2025-report
Monthly Traffic Safety Analysis
141 CRASHES IN
NEWTON, MA
JANUARY 2025
Total crashes in NEWTON increased from 124 in January 2024 to 141 in January 2025, marking a 13.71% rise year-over-year. The most notable shift was the significant increase in crashes at 25 mph speed limits, which rose by 20 crashes.
141
▲ 13.7%was 124
Total Crash Events
0
Persons Killed
33
▲ 6.5%was 31
Persons Injured
23
▲ 27.8%was 18
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. 9 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 2025-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in NEWTON showed an upward trend, increasing by 17 crashes from 124 in January 2024 to 141 in January 2025. This represents a 13.71% increase in total crashes year-over-year. Fatalities remained at zero in both periods, while total injuries saw a slight increase of 2, from 31 to 33.
23
Hit-and-Run Crashes — January 2025
▲ 27.8% vs prior (18)
Hit-and-run crashes increased year-over-year, rising from 18 incidents in January 2024 to 23 incidents in January 2025. This represents an increase of 5 crashes. The hit-and-run rate also climbed from 14.5% to 16.3% of total crashes.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
0
Other Killed
3
Pedestrians Injured
29
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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, with the peak day changing from Tuesday (25 crashes) in January 2024 to Friday (29 crashes) in January 2025. The peak hour for crashes also moved from 1 PM (15 crashes) in the prior period to 8 AM (19 crashes) in the current period. Notably, Monday crashes increased by 10, and Friday crashes increased by 11.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero in both January 2024 and January 2025. While the number of serious injury crashes remained constant at 3, minor injury crashes increased by 3, from 12 to 15. Overall, injury crashes (severity A, B, or C) increased from 21 in January 2024 to 24 in January 2025.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Most severe injury per crash record
Top Contributing Factors
Inattention remained the leading contributing factor, increasing by 6 crashes from 27 in January 2024 to 33 in January 2025. Conversely, Driving too fast for conditions saw a decrease of 6 crashes, falling from 10 to 4. No improper driving also increased by 5 crashes, from 17 to 22, indicating a rise in crashes where no improper driving was identified as a factor.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring under clear weather conditions increased significantly from 62 in January 2024 to 92 in January 2025. Correspondingly, crashes on dry road surfaces increased by 34, from 65 to 99. The number of crashes occurring under adverse road surface conditions (wet, snow, ice) decreased from 56 in January 2024 to 39 in January 2025.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 221 to 259 year-over-year. Honda and Toyota remained the top two vehicle makes involved, with Honda increasing from 32 to 40 and Toyota from 32 to 36. Among persons involved, there was a notable decrease in the 0-15 age group (from 45 to 11) and the 16-20 age group (from 40 to 24).
Top Vehicle Makes (259 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Vehicle unit records
57 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (264 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 25 mph speed zones saw a significant increase, rising by 20 crashes from 47 in January 2024 to 67 in January 2025. Crashes in 55 mph zones also increased slightly from 17 to 19. Conversely, crashes in 30 mph zones decreased by 2, from 23 to 21.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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 2025-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-01-31 (31 days)
- Geographic scope: NEWTON, MA
- Total crash records analyzed: 141
- Total persons involved: 312
- Total vehicles involved: 259
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: January 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/newton/january-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: 2025-01-01 – 2025-01-31
Generated: June 21, 2026 · All rights reserved