ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · PEABODY, MA · MARCH 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/march-2025-report
Monthly Traffic Safety Analysis
99 CRASHES IN
PEABODY, MA
MARCH 2025
In March 2025, Peabody experienced 99 total crashes, a substantial increase compared to the 48 crashes recorded in March 2024. This represents a 106.25% rise in total crash incidents year-over-year. A notable shift is the absence of fatalities in March 2025, down from two fatalities in the prior year.
99
▲ 106.3%was 48
Total Crash Events
0
▼ -100.0%was 2
Persons Killed
40
▲ 207.7%was 13
Persons Injured
11
▲ 266.7%was 3
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 · 2025-03-01 to 2025-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a significant increase in crash incidents in Peabody, with total crashes rising from 48 in March 2024 to 99 in March 2025. This marks a 106.25% increase year-over-year, suggesting a substantial uptick in traffic incidents.
11
Hit-and-Run Crashes — March 2025
▲ 266.7% vs prior (3)
Hit-and-run crashes increased from 3 in March 2024 to 11 in March 2025. The hit-and-run rate also rose from 6.3% in the prior period to 11.1% in the current period, indicating an upward trend in these types of incidents.
Vulnerable Road User Casualties
0
Motorists Killed
40
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · 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 Friday with 10 crashes in March 2024 to Thursday with 17 crashes in March 2025. Similarly, the peak hour changed from 4 PM with 6 crashes in the prior period to 2 PM with 13 crashes in the current period. Crashes on all days of the week increased year-over-year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes decreased from 2 in March 2024 to 0 in March 2025, resulting in the fatal crash rate dropping from 4.17% to 0%. Minor injury crashes increased from 8 to 18, while possible injury crashes remained stable at 3 between both periods. The proportion of crashes resulting in no injury increased slightly from 72.9% to 76.8% year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Most severe injury per crash record
Top Contributing Factors
Contributing factors saw notable changes in crash counts: 'No improper driving' increased by 14 crashes (from 14 to 28), 'Inattention' increased by 9 crashes (from 8 to 17), 'Followed too closely' increased by 5 crashes (from 3 to 8), and 'Failed to yield right of way' increased by 7 crashes (from 1 to 8). Conversely, 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased by 3 crashes (from 6 to 3).
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 26 to 67, while those in cloudy and rainy conditions remained relatively stable. Crashes during daylight hours increased from 35 to 77, and crashes on dry road surfaces rose from 33 to 86. The number of crashes on wet road surfaces decreased slightly from 14 to 13.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 93 to 203 year-over-year. Toyota and Honda remained the top two vehicle makes involved, with Toyota increasing from 22 to 37 and Honda from 17 to 30. The 26-34 age group saw a substantial increase in persons involved, rising from 20 to 48, and the proportion of males involved in crashes increased from 58.4% to 62%.
Top Vehicle Makes (203 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Vehicle unit records
27 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (208 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph zones saw a significant increase, rising from 5 to 35 incidents, and crashes in 30 mph zones increased from 8 to 21. Conversely, crashes in 55 mph zones decreased from 15 to 8, and those in 50 mph zones decreased from 14 to 11. There were no fatalities in any speed zone in March 2025, compared to one fatality in a 50 mph zone in March 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · 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: 2025-03-01 through 2025-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-03-01 through 2025-03-31 (31 days)
- Geographic scope: PEABODY, MA
- Total crash records analyzed: 99
- Total persons involved: 236
- Total vehicles involved: 203
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: March 2025." Published June 21, 2026. Reporting period: 2025-03-01 to 2025-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/peabody/march-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: 2025-03-01 – 2025-03-31
Generated: June 21, 2026 · All rights reserved