Monthly Traffic Safety Analysis

127 CRASHES IN
NEWTON, MA
APRIL 2026

All metrics benchmarked againstApril 2025

The total number of crashes in April 2026 was 127, a decrease of 15.9% compared to the 151 crashes reported in April 2025. The most notable shift was a significant decrease in crashes attributed to "No improper driving," which fell by 46.7% year-over-year.

127

-15.9%was 151

Total Crash Events

0

Persons Killed

32

18.5%was 27

Persons Injured

15

-16.7%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. 6 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes decreased from 151 in April 2025 to 127 in April 2026, representing a 15.9% reduction year-over-year. This indicates a downward trend in overall crash incidents for the month.

15

Hit-and-Run Crashes — April 2026

-16.7% vs prior (18)

The number of hit-and-run crashes decreased from 18 in April 2025 to 15 in April 2026. The hit-and-run rate also saw a minor decrease, moving from 11.9% in April 2025 to 11.8% in April 2026.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

0

Other Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 250.0%

2

Cyclists Injured

Prior: 3-33.3%

25

Motorists Injured

Prior: 2213.6%

2

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · 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 Wednesday (33 crashes) in April 2025 to Friday (26 crashes) in April 2026. The peak hour also changed, moving from 5 PM (15 crashes) in April 2025 to 4 PM (13 crashes) in April 2026.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both April 2025 and April 2026. Total injuries increased from 27 persons in April 2025 to 32 persons in April 2026. The proportion of crashes resulting in minor injuries (Severity B) increased from 10.6% in April 2025 to 16.5% in April 2026.

Outcome by Severity (Crash Events)

Minor Injury21minor injury crashes16.5%
31.3%prior 16
Possible Injury6possible injury crashes4.7%
-25.0%prior 8
No Injury94no injury crashes74%
-21.7%prior 120

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "Inattention" increased from 33 in April 2025 to 42 in April 2026, a 27.3% rise in count. Conversely, crashes with "No improper driving" as a factor significantly decreased from 30 to 16, a 46.7% reduction in count. "Failed to yield right of way" also saw a substantial decrease, falling from 13 crashes to 7 crashes, a 46.2% reduction in count.

Officer-Reported Primary Contributing Cause

Inattention42 (33.1%)27.3%prior 33
Followed too closely17 (13.4%)-5.6%prior 18
No improper driving16 (12.6%)-46.7%prior 30
Failure to keep in proper lane or running off road9 (7.1%)50.0%prior 6
Failed to yield right of way7 (5.5%)-46.2%prior 13
Disregarded traffic signs, signals, road markings4 (3.1%)
Driving too fast for conditions4 (3.1%)
Distracted4 (3.1%)
Other improper action3 (2.4%)-40.0%prior 5
Fatigued/asleep3 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The number of crashes occurring in clear weather conditions decreased from 116 in April 2025 to 92 in April 2026. Crashes on dry road surfaces decreased from 120 to 100, while those on wet surfaces decreased from 29 to 26. Daylight conditions remained the dominant lighting factor, with 99 crashes in April 2026 compared to 119 in April 2025.

Weather

Clear75 (59.5%)
-19.4%prior 93
Clear/Clear17 (13.5%)
-26.1%prior 23
Cloudy14 (11.1%)
133.3%prior 6
Rain10 (7.9%)
-41.2%prior 17
Cloudy/Rain3 (2.4%)
Rain/Cloudy3 (2.4%)
Rain/Rain2 (1.6%)
Clear/Cloudy1 (0.8%)
Rain/Clear1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Weather condition at time of crash

Lighting

Daylight99 (78.6%)
-16.8%prior 119
Dark - lighted roadway21 (16.7%)
5.0%prior 20
Dusk3 (2.4%)
-40.0%prior 5
Dawn1 (0.8%)
Dark - roadway not lighted1 (0.8%)
Dark - unknown roadway lighting1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Lighting condition field

Road Surface

Dry100 (78.7%)
-16.7%prior 120
Wet26 (20.5%)
-10.3%prior 29
Ice1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 297 in April 2025 to 243 in April 2026. Toyota remained the most frequently involved make, though its count decreased from 51 to 44, and Honda also saw a decrease from 39 to 29. The age group 0-15 saw a significant drop in persons involved, from 39 to 9, while the 55-64 age group increased from 30 to 43 persons.

Top Vehicle Makes (243 vehicles)

1
TOYOTA44 (18.1%)
-13.7%prior 51
2
HONDA29 (11.9%)
-25.6%prior 39
3
FORD18 (7.4%)
-18.2%prior 22
4
SUBARU16 (6.6%)
0.0%prior 16
5
CHEVROLET13 (5.3%)
44.4%prior 9
6
VOLKSWAGEN10 (4.1%)
7
HYUNDAI10 (4.1%)
-37.5%prior 16
8
AUDI8 (3.3%)
0.0%prior 8
9
MERCEDES-BENZ7 (2.9%)
-12.5%prior 8
10
LEXUS6 (2.5%)
-45.5%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Vehicle unit records

33 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (254 persons with recorded sex)

Male141 (55.5%)
-23.4%prior 184
Female113 (44.5%)
-29.4%prior 160

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 25 mph speed zones decreased from 82 in April 2025 to 70 in April 2026. Similarly, crashes in 30 mph zones decreased from 24 to 14, and in 55 mph zones from 18 to 16. Fatal crashes remained at 0 across all speed zones for both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · 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: 2026-04-01 through 2026-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2026-04-01 through 2026-04-30 (30 days)
  • Geographic scope: NEWTON, MA
  • Total crash records analyzed: 127
  • Total persons involved: 285
  • Total vehicles involved: 243

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: April 2026." Published June 21, 2026. Reporting period: 2026-04-01 to 2026-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/newton/april-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

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Newton, MA Crash Report — April 2026 | ThatCarHitMe.com