ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · PEABODY, MA · 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/2023-annual-report
Yearly Traffic Safety Analysis
1,372 CRASHES IN
PEABODY, MA
2023
In 2023, Peabody recorded 1,372 total crashes, a 5.8% increase from the 1,297 crashes reported in 2022. Despite the rise in overall collisions, the number of resulting injuries saw a notable decrease of 15.8%, falling from 448 to 377 year-over-year. The number of fatalities also decreased from two in 2022 to one in 2023.
1,372
▲ 5.8%was 1,297
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
377
▼ -15.8%was 448
Persons Injured
72
▲ 24.1%was 58
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 66 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash data for Peabody indicates a rising trend in the total number of collisions, with a 5.8% increase from 1,297 in 2022 to 1,372 in 2023. However, the severity of these incidents trended downward, as total injuries declined by 15.8% and fatalities fell from two to one over the same period.
72
Hit-and-Run Crashes — 2023
▲ 24.1% vs prior (58)
Hit-and-run incidents in Peabody trended upward in 2023 compared to the previous year. The total number of hit-and-run crashes increased by 24.1%, from 58 in 2022 to 72 in 2023. This rise is also reflected in the hit-and-run rate, which grew from 4.5% of all crashes in 2022 to 5.2% in 2023.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
13
Pedestrians Injured
9
Cyclists Injured
352
Motorists Injured
3
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes in Peabody shifted between 2022 and 2023. The peak day for collisions moved from Friday (205 crashes) in 2022 to Monday (217 crashes) in 2023. Similarly, the peak hour for crashes occurred an hour earlier, shifting from 3 PM in the prior year to 2 PM in the current year, which saw 122 incidents during that hour.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity in Peabody decreased year-over-year. The number of fatal crashes dropped from two in 2022 to one in 2023, and the proportion of crashes resulting in any level of injury (Serious, Minor, or Possible) fell from 25.3% to 20.3%. Correspondingly, the share of property-damage-only (No Injury) crashes increased from 71.0% in 2022 to 74.9% in 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes in Peabody remained consistent, with 'No improper driving,' 'Inattention,' and 'Followed too closely' as the top three in both 2022 and 2023. However, the counts for some key factors shifted; crashes attributed to 'Inattention' decreased by 5.6% (from 266 to 251), while those involving 'Failed to yield right of way' increased by 15.9% (from 82 to 95). Notably, crashes where 'Distracted' driving was a factor saw an 88.2% increase in count, rising from 17 incidents in 2022 to 32 in 2023.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of crashes by lighting conditions remained stable year-over-year, with approximately 69% of incidents in both periods occurring in daylight. However, there was a notable shift in crashes occurring during adverse surface and weather conditions. The number of crashes on wet roads increased by 45.1%, from 153 in 2022 to 222 in 2023. Similarly, collisions during rain rose by 69.1%, from 68 to 115 incidents.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The vehicle makes most frequently involved in crashes showed little change year-over-year, with Toyota, Honda, and Ford consistently ranking as the top three in both 2022 and 2023. The age demographics of persons involved in collisions also remained largely stable. The proportional representation of most age groups saw minimal fluctuation, with no single group experiencing a significant shift in its share of total persons involved.
Top Vehicle Makes (2,656 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
221 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,800 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in Peabody continue to be concentrated in lower speed zones, with 25 mph and 30 mph zones accounting for the highest volumes in both 2022 and 2023. There was a 20.9% increase in collisions within 25 mph zones, rising from 316 to 382. All fatal crashes recorded in both years occurred in 25 mph zones, with two in 2022 and one in 2023.
Fatal crashes by zone: 25 mph: 1 of 382 (0.262%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: PEABODY, MA
- Total crash records analyzed: 1,372
- Total persons involved: 3,084
- Total vehicles involved: 2,656
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/peabody/2023-annual-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved