ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · PEABODY, MA · APRIL 2023
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-2023-report
Monthly Traffic Safety Analysis
112 CRASHES IN
PEABODY, MA
APRIL 2023
In April 2023, Peabody experienced 112 total crashes, an increase from 102 crashes reported in April 2022, representing a 9.8% rise year-over-year. The most notable shift was a significant increase in DUI-related crashes, which more than doubled from 3 in April 2022 to 7 in April 2023.
112
▲ 9.8%was 102
Total Crash Events
0
Persons Killed
37
▲ 12.1%was 33
Persons Injured
10
▲ 100.0%was 5
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 · 2023-04-01 to 2023-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the trend for crashes in Peabody is upward, with total crashes increasing from 102 in April 2022 to 112 in April 2023. This represents a 9.8% increase in total crash incidents year-over-year. Total injuries also increased from 33 to 37 during the same period.
10
Hit-and-Run Crashes — April 2023
▲ 100.0% vs prior (5)
Hit-and-run crashes increased significantly, rising from 5 in April 2022 to 10 in April 2023. This change led to a doubling of the hit-and-run rate, from 4.9% in April 2022 to 8.9% in April 2023, indicating an upward trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
3
Pedestrians Injured
3
Cyclists Injured
31
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Tuesday in both periods, with 21 crashes recorded on this day in both April 2022 and April 2023. However, the peak hour shifted from 4 PM with 14 crashes in April 2022 to 3 PM with 13 crashes in April 2023. While the peak day remained consistent, the peak hour experienced a slight shift.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either April 2022 or April 2023. Serious injury crashes (severity A) increased from 1 (1.0% of total crashes) in April 2022 to 2 (1.8% of total crashes) in April 2023. Minor injury crashes (severity B) remained constant at 13 in both periods, though their share decreased from 12.7% to 11.6% of total crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to 'Inattention' decreased by 6, from 25 in April 2022 to 19 in April 2023. Conversely, 'Followed too closely' crashes more than doubled, increasing by 8 from 6 in April 2022 to 14 in April 2023. 'Failure to keep in proper lane or running off road' also saw a substantial increase, rising from 1 crash in April 2022 to 7 crashes in April 2023.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Rain' conditions increased from 5 in April 2022 to 8 in April 2023. The number of crashes on 'Wet' road surfaces more than doubled, rising from 8 in April 2022 to 17 in April 2023. Crashes occurring in 'Dark - lighted roadway' conditions also increased, from 18 to 26 year-over-year.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Road surface condition field
Vehicles & Demographics
The age group 45-54 saw a significant decrease in persons involved in crashes, dropping from 34 in April 2022 to 18 in April 2023. Conversely, the 65+ age group experienced a substantial increase, from 17 persons in April 2022 to 38 persons in April 2023. The number of males involved in crashes increased from 109 to 126, while females decreased from 105 to 84.
Top Vehicle Makes (200 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Vehicle unit records
23 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (210 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph zones increased from 28 in April 2022 to 30 in April 2023. Crashes in 30 mph zones also rose, from 18 to 24 year-over-year. There were no fatal crashes reported in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · 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: 2023-04-01 through 2023-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-04-01 through 2023-04-30 (30 days)
- Geographic scope: PEABODY, MA
- Total crash records analyzed: 112
- Total persons involved: 237
- Total vehicles involved: 200
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 2023." Published June 21, 2026. Reporting period: 2023-04-01 to 2023-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/peabody/april-2023-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: 2023-04-01 – 2023-04-30
Generated: June 21, 2026 · All rights reserved