ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · PEABODY, MA · JUNE 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/peabody/june-2025-report
Monthly Traffic Safety Analysis
120 CRASHES IN
PEABODY, MA
JUNE 2025
PEABODY experienced a significant increase in crash activity in June 2025 compared to June 2024, with total crashes rising by 60% from 75 to 120. Total injuries also increased by 35.7%, from 28 to 38. Fatalities remained at zero for both periods.
120
▲ 60.0%was 75
Total Crash Events
0
Persons Killed
38
▲ 35.7%was 28
Persons Injured
8
▲ 14.3%was 7
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. 2 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
The overall trend indicates a notable increase in crash incidents year-over-year, with total crashes rising from 75 in June 2024 to 120 in June 2025, representing a 60% increase. Similarly, total injuries increased by 35.7% from 28 to 38 during the same period. Fatalities remained stable at zero in both months.
8
Hit-and-Run Crashes — June 2025
▲ 14.3% vs prior (7)
The number of hit-and-run crashes increased from 7 in June 2024 to 8 in June 2025. Despite this, the overall hit-and-run rate decreased from 9.3% to 6.7% of total crashes.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
1
Cyclists Injured
36
Motorists Injured
1
Other Injured
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 Sunday in June 2024, with 15 incidents, to Wednesday in June 2025, with 26 incidents. The peak hour also changed, moving from 5 PM with 8 crashes in the prior period to 4 PM with 17 crashes in the current period.
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
While fatal crashes remained at zero in both periods, total injuries increased from 28 to 38 year-over-year. The number of serious injury crashes remained constant at 1, though its share of total crashes decreased from 1.3% to 0.8%. Minor injury crashes increased from 16 to 21, but their share decreased from 21.3% to 17.5% of total crashes.
Outcome by Severity (Crash Events)
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
Several contributing factors saw notable increases in crash counts year-over-year. 'No improper driving' crashes increased from 20 to 45 (a 125% increase in count), 'Inattention' crashes rose from 16 to 27 (a 68.75% increase in count), and 'Followed too closely' crashes grew from 9 to 17 (an 88.9% increase in count). Conversely, 'Failed to yield right of way' crashes decreased from 6 to 2 (a 66.7% decrease in count).
Officer-Reported Primary Contributing Cause
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 'Clear' weather conditions significantly increased from 51 to 91 year-over-year, while 'Rain' related crashes decreased from 4 to 3. Similarly, crashes during 'Daylight' conditions rose from 58 to 103, and those on 'Dry' road surfaces increased from 67 to 114. Crashes on 'Wet' road surfaces decreased from 8 to 5.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes increased from 188 to 289 year-over-year. The 65+ age group saw a significant increase in involved persons from 18 to 46, and the 35-44 age group increased from 32 to 50 persons. Honda became the top vehicle make involved, increasing from 22 to 43, while Toyota, previously first, increased from 23 to 38.
Top Vehicle Makes (248 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Vehicle unit records
25 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (258 persons with recorded sex)
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 saw a substantial increase from 19 to 45 year-over-year. Crashes in 30 mph zones also rose from 15 to 24, and those in 55 mph zones increased from 9 to 19. All speed zones continued to report zero fatal crashes in both periods.
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: PEABODY, MA
- Total crash records analyzed: 120
- Total persons involved: 289
- Total vehicles involved: 248
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). "PEABODY, 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/peabody/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-06-01 – 2025-06-30
Generated: June 21, 2026 · All rights reserved