ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · NEWTON, MA · 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/2024-annual-report
Yearly Traffic Safety Analysis
1,706 CRASHES IN
NEWTON, MA
2024
In Newton, total traffic crashes increased by 2.5% from 1,665 in 2023 to 1,706 in 2024. Despite the rise in crash volume, total fatalities decreased from 2 to 1, and total injuries fell from 398 to 378. The most significant year-over-year change was a 54.2% reduction in crashes resulting in a serious injury, which dropped from 24 to 11.
1,706
▲ 2.5%was 1,665
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
378
▼ -5.0%was 398
Persons Injured
216
▲ 2.4%was 211
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 107 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Newton show a mixed signal. The total number of crashes rose slightly by 2.5% year-over-year, from 1,665 to 1,706. However, the severity of these incidents decreased, with total injuries declining by 5.0% (from 398 to 378) and fatalities being cut in half from 2 to 1.
216
Hit-and-Run Crashes — 2024
▲ 2.4% vs prior (211)
Hit-and-run incidents remained a stable issue year-over-year. The absolute number of hit-and-run crashes saw a minor increase from 211 in 2023 to 216 in 2024. However, the hit-and-run rate as a percentage of all crashes held steady at 12.7% for both periods, indicating no change in the proportional trend.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
27
Pedestrians Injured
23
Cyclists Injured
323
Motorists Injured
5
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. In 2024, the peak day for crashes was Friday with 278 incidents, a change from Thursday (286 incidents) in the prior year. The peak hour also moved earlier, from 5 p.m. (185 crashes) in 2023 to 3 p.m. (146 crashes) in 2024, indicating a less concentrated evening rush hour peak.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes decreased from 2023 to 2024. The fatal crash rate was halved, dropping from 0.12% to 0.06%. Most notably, the count of serious injury crashes fell by 54.2%, from 24 to 11, and their share of all crashes decreased from 1.4% to 0.6%. This was accompanied by an increase in the proportion of minor injury crashes, which rose from 11.3% to 12.5% of all incidents.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes shifted significantly year-over-year. 'Inattention' became the top factor in 2024, with its count increasing by 51.5% from 291 to 441 crashes. This displaced 'No improper driving,' which saw its count fall by 26.7% from 345 to 253. 'Followed too closely' remained the third-ranked factor, with a stable count increasing slightly from 212 to 221.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in 2024 were slightly more concentrated in clear conditions compared to the previous year. The proportion of crashes occurring on dry road surfaces increased from 77.4% in 2023 to 81.2% in 2024. Correspondingly, crashes on wet surfaces decreased, accounting for 14.3% of incidents in 2024, down from 18.9% in the prior year. Lighting conditions for crashes remained nearly identical, with daylight crashes making up 71.9% of the total in both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes remained consistent, with Toyota and Honda leading in both 2023 and 2024. Toyota-involved crashes increased from 526 to 562, and Honda-involved crashes were stable at 418 and 421, respectively. Demographically, the 26-34 age group was the most frequently involved cohort in both periods, though their count decreased from 642 to 611 persons. Overall age distributions showed no major shifts.
Top Vehicle Makes (3,152 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
407 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (3,600 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crash locations shifted toward lower speed zones in 2024. Crashes in 25 mph zones increased from 701 to 789, while incidents in 30 mph and 55 mph zones saw decreases. The single fatal crash in 2024 occurred in a 25 mph zone. This contrasts with 2023, which recorded one fatality in a 5 mph zone and another in a 25 mph zone.
Fatal crashes by zone: 25 mph: 1 of 789 (0.127%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: NEWTON, MA
- Total crash records analyzed: 1,706
- Total persons involved: 4,035
- Total vehicles involved: 3,152
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/newton/2024-annual-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: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved