ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEWTON, MA · SEPTEMBER 2024
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/september-2024-report
Monthly Traffic Safety Analysis
134 CRASHES IN
NEWTON, MA
SEPTEMBER 2024
Total crashes in NEWTON decreased by 8.84% year-over-year, from 147 in September 2023 to 134 in September 2024. During the same period, total injuries saw a more significant reduction of 25.64%, dropping from 39 to 29. The most notable shift was the substantial increase in crashes attributed to 'Inattention', which rose from 19 to 47 incidents.
134
▼ -8.8%was 147
Total Crash Events
0
Persons Killed
29
▼ -25.6%was 39
Persons Injured
20
▲ 33.3%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 · 2024-09-01 to 2024-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a decrease in crash incidents, with total crashes falling by 8.84% from 147 to 134 year-over-year. Concurrently, the number of injured persons also declined, reflecting a positive trend in crash outcomes.
20
Hit-and-Run Crashes — September 2024
▲ 33.3% vs prior (15)
The number of hit-and-run crashes increased by 5, from 15 in September 2023 to 20 in September 2024. This resulted in an increase in the hit-and-run rate, which rose from 10.2% to 14.9% year-over-year.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
5
Cyclists Injured
24
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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 September 2023 (29 crashes) to Thursday in September 2024 (28 crashes). The peak hour also changed, moving from 4 PM in the prior period to 1 PM in the current period, with both hours recording 15 crashes. This suggests a shift in the times of day when crashes are most frequent.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes or fatalities reported in either September 2023 or September 2024. Serious injuries (Severity A) decreased by 50% from 2 crashes to 1 crash year-over-year. Minor injuries (Severity B) also saw a reduction, decreasing by 18.18% from 22 crashes to 18 crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, 'Inattention', increased significantly by 28 crashes, rising from 19 in September 2023 to 47 in September 2024, and its share of crashes grew from 12.9% to 35.1%. Conversely, 'No improper driving' decreased by 12 crashes, from 33 to 21, and 'Followed too closely' decreased by 5 crashes, from 18 to 13. These shifts indicate a change in the primary reported causes of crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring under clear weather conditions increased by 10, from 89 to 99, while crashes in rainy conditions decreased by 7, from 16 to 9. Similarly, crashes on wet road surfaces decreased by 16, from 28 to 12. There was a notable decrease of 6 crashes occurring at dusk, from 6 to 0, suggesting fewer incidents during transitional lighting conditions.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased by 28, from 272 to 244. While Toyota and Honda remained the top two vehicle makes involved, crashes involving Jeep vehicles saw a decrease of 9, from 15 to 6. There was a significant increase of 37 persons aged 0-15 involved in crashes, rising from 19 to 56, and a decrease of 22 persons aged 26-34, from 59 to 37.
Top Vehicle Makes (244 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Vehicle unit records
24 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (308 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 MPH zones saw a slight increase of 2, from 58 to 60, and 30 MPH zones increased by 4, from 24 to 28. The most significant change was a decrease of 13 crashes in 55 MPH zones, falling from 33 to 20. There were no fatal crashes reported in any speed zone for either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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: 2024-09-01 through 2024-09-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-09-01 through 2024-09-30 (30 days)
- Geographic scope: NEWTON, MA
- Total crash records analyzed: 134
- Total persons involved: 344
- Total vehicles involved: 244
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: September 2024." Published June 21, 2026. Reporting period: 2024-09-01 to 2024-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/newton/september-2024-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: 2024-09-01 – 2024-09-30
Generated: June 21, 2026 · All rights reserved