ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · PEABODY, MA · OCTOBER 2024
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/october-2024-report
Monthly Traffic Safety Analysis
106 CRASHES IN
PEABODY, MA
OCTOBER 2024
Total crashes in October 2024 were 106, a decrease of 19.7% compared to 132 crashes in October 2023. A significant positive shift was observed in fatalities, which decreased from 1 in October 2023 to 0 in October 2024. Total injuries, however, increased by 7, from 34 to 41.
106
▼ -19.7%was 132
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
41
▲ 20.6%was 34
Persons Injured
4
▼ -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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in October 2024 decreased compared to October 2023. The total number of crashes fell by 26, representing a 19.7% reduction year-over-year. This indicates a downward trend in overall crash incidents for the month.
4
Hit-and-Run Crashes — October 2024
▼ -42.9% vs prior (7)
Hit-and-run crashes decreased from 7 in October 2023 to 4 in October 2024. Correspondingly, the hit-and-run rate also decreased from 5.3% of total crashes to 3.8% year-over-year. This indicates a downward trend in hit-and-run incidents.
Vulnerable Road User Casualties
0
Motorists Killed
0
Other Killed
40
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Tuesday in both periods, though the count decreased from 23 in October 2023 to 20 in October 2024. The peak crash hour shifted from 12p (17 crashes) in October 2023 to 6p (13 crashes) in October 2024. This indicates a shift in the most frequent hour for crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes decreased from 1 in October 2023 to 0 in October 2024, resulting in a fatal crash rate reduction from 0.76% to 0%. Crashes involving serious injuries decreased from 3 (2.3% of crashes) to 1 (0.9% of crashes) year-over-year. Minor injury crashes remained at 20 in both periods, but their share increased from 15.2% to 18.9%, while possible injury crashes increased from 3 (2.3%) to 7 (6.6%).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Most severe injury per crash record
Top Contributing Factors
Inattention saw the largest increase, rising by 10 crashes from 13 in October 2023 to 23 in October 2024, making it the leading factor. Conversely, 'No improper driving' decreased by 15 crashes, from 37 to 22. 'Followed too closely' remained constant at 16 crashes in both periods.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The number of crashes occurring in 'Clear' weather conditions decreased from 101 in October 2023 to 75 in October 2024. Crashes on 'Wet' road surfaces decreased from 11 to 7 year-over-year. Crashes occurring in 'Dark - lighted roadway' conditions also saw a reduction, from 38 in October 2023 to 25 in October 2024.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 254 in October 2023 to 213 in October 2024. While Toyota remained the most frequently involved make, its count decreased from 44 to 40, and Honda moved into second place with 29 vehicles, up from 28. Notably, crashes involving persons in the 26-34 age group saw a significant decrease, from 60 in October 2023 to 37 in October 2024.
Top Vehicle Makes (213 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Vehicle unit records
22 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (232 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph zones decreased from 33 in October 2023 to 30 in October 2024, and this zone no longer recorded any fatalities, down from 1. The number of crashes in 30 mph zones also decreased from 23 to 20. Overall, there was a general decrease in crash counts across most speed limit categories, with 55 mph zones seeing a slight decrease from 17 to 16 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-10-01 to 2024-10-31 · 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: 2024-10-01 through 2024-10-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-10-01 through 2024-10-31 (31 days)
- Geographic scope: PEABODY, MA
- Total crash records analyzed: 106
- Total persons involved: 256
- Total vehicles involved: 213
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: October 2024." Published June 21, 2026. Reporting period: 2024-10-01 to 2024-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/peabody/october-2024-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: 2024-10-01 – 2024-10-31
Generated: June 21, 2026 · All rights reserved