Monthly Traffic Safety Analysis

168 CRASHES IN
NEWTON, MA
JUNE 2025

All metrics benchmarked againstJune 2024

In June 2025, there were 168 total crashes, an increase from 161 crashes in June 2024, representing a 4.35% rise. The most notable year-over-year shift was the absence of fatalities in June 2025, compared to one fatality in the prior period.

168

4.3%was 161

Total Crash Events

0

-100.0%was 1

Persons Killed

47

11.9%was 42

Persons Injured

24

9.1%was 22

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. 10 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in NEWTON, MA showed a slight increase, rising from 161 in June 2024 to 168 in June 2025, an increase of 4.35%. Despite the rise in total crashes, there was a positive trend in safety outcomes with fatalities decreasing from 1 to 0.

24

Hit-and-Run Crashes — June 2025

9.1% vs prior (22)

Hit-and-run crashes increased from 22 in June 2024 to 24 in June 2025. The hit-and-run rate also saw a slight increase, rising from 13.7% in the prior period to 14.3% in the current period, indicating an upward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1-100.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 30.0%

5

Cyclists Injured

Prior: 425.0%

39

Motorists Injured

Prior: 3414.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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 Tuesday with 38 crashes in June 2024 to Thursday with 30 crashes in June 2025. The peak crash hour also changed, moving from 5 PM with 15 crashes in June 2024 to 3 PM with 21 crashes in June 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased from 1 in June 2024 to 0 in June 2025, and serious injuries also decreased from 1 to 0. Minor injuries increased from 21 to 26, while possible injuries decreased from 14 to 7.

Outcome by Severity (Crash Events)

Minor Injury26minor injury crashes15.5%
23.8%prior 21
Possible Injury7possible injury crashes4.2%
-50.0%prior 14
No Injury125no injury crashes74.4%
12.6%prior 111

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, 'Inattention,' saw a slight increase from 45 crashes in June 2024 to 46 crashes in June 2025, a 2.2% increase in count. 'No improper driving' increased from 21 crashes to 26 crashes, a 23.8% increase in count, causing its ranking to rise. Conversely, 'Followed too closely' decreased from 26 crashes to 23 crashes, an 11.5% decrease in count, leading to a shift in its ranking.

Officer-Reported Primary Contributing Cause

Inattention46 (27.4%)2.2%prior 45
No improper driving26 (15.5%)23.8%prior 21
Followed too closely23 (13.7%)-11.5%prior 26
Failed to yield right of way15 (8.9%)0.0%prior 15
Over-correcting/over-steering6 (3.6%)
Failure to keep in proper lane or running off road5 (3%)-16.7%prior 6
Other improper action5 (3%)-16.7%prior 6
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (2.4%)
Disregarded traffic signs, signals, road markings3 (1.8%)
Made an improper turn3 (1.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in dry road surface conditions increased from 148 in June 2024 to 151 in June 2025, while wet conditions saw a slight increase from 11 to 14 crashes. Daylight conditions remained the dominant lighting factor, with 148 crashes in June 2025 compared to 136 in the prior period.

Weather

Clear112 (67.1%)
-13.2%prior 129
Clear/Clear25 (15.0%)
127.3%prior 11
Cloudy14 (8.4%)
27.3%prior 11
Rain6 (3.6%)
-14.3%prior 7
Cloudy/Cloudy2 (1.2%)
Clear/Cloudy2 (1.2%)
Cloudy/Rain2 (1.2%)
Rain/Cloudy2 (1.2%)
Rain/Rain1 (0.6%)
Cloudy/Clear1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Weather condition at time of crash

Lighting

Daylight148 (89.7%)
8.8%prior 136
Dark - lighted roadway17 (10.3%)
13.3%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Lighting condition field

Road Surface

Dry151 (91.5%)
2.0%prior 148
Wet14 (8.5%)
27.3%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Road surface condition field

Vehicles & Demographics

The age group 26-34 experienced an increase in representation, from 44 persons in June 2024 to 56 persons in June 2025. Similarly, the 45-54 age group saw an increase from 36 persons to 56 persons. The top three vehicle makes remained consistent, with TOYOTA, HONDA, and FORD showing increased counts in June 2025.

Top Vehicle Makes (323 vehicles)

1
TOYOTA62 (19.2%)
26.5%prior 49
2
HONDA46 (14.2%)
35.3%prior 34
3
FORD36 (11.1%)
80.0%prior 20
4
SUBARU13 (4%)
-7.1%prior 14
5
HYUNDAI13 (4%)
160.0%prior 5
6
LEXUS12 (3.7%)
20.0%prior 10
7
NISSAN11 (3.4%)
-8.3%prior 12
8
BMW10 (3.1%)
-37.5%prior 16
9
CHEVROLET10 (3.1%)
-33.3%prior 15
10
MERCEDES-BENZ9 (2.8%)
0.0%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Vehicle unit records

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

Sex Distribution (358 persons with recorded sex)

Male196 (54.7%)
10.7%prior 177
Female162 (45.3%)
22.7%prior 132

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph speed zones increased significantly from 67 in June 2024 to 91 in June 2025, with no fatal crashes reported in this zone during the current period, compared to one fatal crash in the prior period. Crashes in 55 mph speed zones decreased from 32 to 26 year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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: 2025-06-01 through 2025-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-06-01 through 2025-06-30 (30 days)
  • Geographic scope: NEWTON, MA
  • Total crash records analyzed: 168
  • Total persons involved: 407
  • Total vehicles involved: 323

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: June 2025." Published June 21, 2026. Reporting period: 2025-06-01 to 2025-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/newton/june-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

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Newton, MA Crash Report — June 2025 | ThatCarHitMe.com