ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · PEABODY, MA · APRIL 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/april-2025-report
Monthly Traffic Safety Analysis
114 CRASHES IN
PEABODY, MA
APRIL 2025
In April 2025, Peabody experienced 114 crashes, an increase of 40.74% compared to the 81 crashes recorded in April 2024. This notable rise in overall crash incidents is the most significant year-over-year shift observed.
114
▲ 40.7%was 81
Total Crash Events
0
Persons Killed
33
▲ 43.5%was 23
Persons Injured
10
▲ 42.9%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. 8 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for April 2025 indicates an upward trend in Peabody, with total crashes increasing by 40.74% from 81 to 114 incidents compared to April 2024. Concurrently, total injuries rose by 43.48%, from 23 to 33, while fatalities remained at zero in both periods.
10
Hit-and-Run Crashes — April 2025
▲ 42.9% vs prior (7)
Hit-and-run crashes increased by 42.9%, from 7 incidents in April 2024 to 10 incidents in April 2025. The hit-and-run rate also saw a slight increase, moving from 8.6% of total crashes in the prior period to 8.8% in the current period, indicating a minor upward trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
2
Pedestrians Injured
4
Cyclists Injured
27
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · 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 Tuesday in April 2024, with 20 incidents, to Wednesday in April 2025, with 25 incidents. The peak hour for crashes remained consistent, with 13 crashes at 2p in April 2024 and 13 crashes at 3p in April 2025.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities remained at zero in both April 2024 and April 2025. The proportion of 'No Injury' crashes decreased from 75.3% of total crashes in April 2024 to 70.2% in April 2025. Conversely, 'Minor Injury' crashes saw an increase in their proportion, rising from 12.3% to 17.5% year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor shifted from 'Inattention' in April 2024 (19 crashes) to 'No improper driving' in April 2025 (32 crashes), representing an 88.2% increase in this category. 'Inattention' crashes saw a slight increase from 19 to 20 incidents, while 'Followed too closely' crashes decreased by 26.7%, from 15 incidents to 11 incidents year-over-year.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The proportion of crashes occurring in 'Clear' weather decreased from 72.8% in April 2024 to 66.7% in April 2025, while crashes on 'Wet' road surfaces increased in proportion from 8.6% to 13.2%. Crashes occurring during 'Daylight' hours decreased from 88.9% to 76.3%, with a corresponding increase in crashes occurring in 'Dark - lighted roadway' conditions from 8.6% to 15.8%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Road surface condition field
Vehicles & Demographics
The leading vehicle make involved in crashes shifted from HONDA in April 2024 (28 vehicles) to TOYOTA in April 2025 (35 vehicles), an increase of 29.6% for TOYOTA. HONDA vehicles involved in crashes increased by 17.9% to 33, while FORD vehicles saw a 91.7% increase, rising from 12 to 23 vehicles year-over-year.
Top Vehicle Makes (224 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Vehicle unit records
33 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (242 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph zones significantly increased by 95.2%, rising from 21 incidents in April 2024 to 41 in April 2025. Similarly, 30 mph zones saw a 43.8% increase in crashes, from 16 to 23 incidents. Conversely, crashes in higher speed zones decreased, with 55 mph zones experiencing a 37.5% reduction from 16 to 10 incidents, and 50 mph zones decreasing by 30.8% from 13 to 9 incidents.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · 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: 2025-04-01 through 2025-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-04-01 through 2025-04-30 (30 days)
- Geographic scope: PEABODY, MA
- Total crash records analyzed: 114
- Total persons involved: 277
- Total vehicles involved: 224
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: April 2025." Published June 21, 2026. Reporting period: 2025-04-01 to 2025-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/peabody/april-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: 2025-04-01 – 2025-04-30
Generated: June 21, 2026 · All rights reserved