ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · PEABODY, MA · NOVEMBER 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/november-2023-report
Monthly Traffic Safety Analysis
111 CRASHES IN
PEABODY, MA
NOVEMBER 2023
In November 2023, Peabody experienced 111 crashes, a 14.4% increase compared to 97 crashes in November 2022. A notable shift includes the complete elimination of speeding-related crashes, which dropped from 5 in the prior period to 0 in the current period.
111
▲ 14.4%was 97
Total Crash Events
0
Persons Killed
29
▼ -14.7%was 34
Persons Injured
6
▼ -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. 7 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash incidents in Peabody are rising year-over-year, with total crashes increasing by 14.4% from 97 in November 2022 to 111 in November 2023. Despite this increase in total crashes, total injuries decreased by 14.7%, from 34 to 29.
6
Hit-and-Run Crashes — November 2023
▼ -14.3% vs prior (7)
The number of hit-and-run crashes decreased from 7 in November 2022 to 6 in November 2023. The hit-and-run crash rate also saw a decline, moving from 7.2% of all crashes in the prior period to 5.4% in the current period, indicating a downward trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
3
Pedestrians Injured
1
Cyclists Injured
25
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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 Wednesday in both periods, though the number of crashes on Wednesdays decreased from 27 in November 2022 to 20 in November 2023. The peak hour shifted from 3 PM with 16 crashes in the prior period to 2 PM with 15 crashes in the current period. Notably, crashes during the 10 AM hour increased from 0 to 6, and during the 4 PM hour from 5 to 13.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes or fatalities in either November 2023 or November 2022. Serious injury crashes increased from 1 in the prior period to 2 in the current period, representing a 100% rise. Minor injury crashes decreased from 15 to 14, while possible injury crashes increased from 6 to 8.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor in both periods was "No improper driving," though its count decreased from 32 in November 2022 to 29 in November 2023. "Inattention" also saw a decrease, from 21 crashes to 17 crashes. A notable increase was observed in "Failed to yield right of way" crashes, which rose from 5 in the prior period to 14 in the current period, while "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" decreased from 6 to 3.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased significantly from 63 in November 2022 to 86 in November 2023, while crashes in rainy conditions decreased from 7 to 3. Correspondingly, crashes on dry road surfaces rose from 78 to 104, and those on wet surfaces decreased from 17 to 7. Crashes in dark-lighted roadway conditions also increased, from 27 to 37.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 178 in November 2022 to 216 in November 2023. Toyota remained the most involved make, increasing from 30 to 38 vehicles, while Honda increased from 31 to 33. Regarding persons involved, the 16-20 age group saw a notable increase from 19 to 30, and the 45-54 age group increased from 18 to 32.
Top Vehicle Makes (216 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Vehicle unit records
13 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (229 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 25 MPH zones significantly increased from 22 in November 2022 to 34 in November 2023, and crashes in 50 MPH zones rose from 5 to 13. Conversely, crashes in 55 MPH zones decreased substantially from 16 to 6, and in 15 MPH zones from 7 to 3. There were no fatal crashes reported in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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: 2023-11-01 through 2023-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-11-01 through 2023-11-30 (30 days)
- Geographic scope: PEABODY, MA
- Total crash records analyzed: 111
- Total persons involved: 247
- Total vehicles involved: 216
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: November 2023." Published June 21, 2026. Reporting period: 2023-11-01 to 2023-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/peabody/november-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: 2023-11-01 – 2023-11-30
Generated: June 21, 2026 · All rights reserved