Monthly Traffic Safety Analysis

131 CRASHES IN
PEABODY, MA
JUNE 2023

All metrics benchmarked againstJune 2022

In June 2023, Peabody experienced 131 crashes, an increase of 15.93% compared to the 113 crashes in June 2022. This period saw a significant rise in hit-and-run incidents, which more than doubled year-over-year.

131

15.9%was 113

Total Crash Events

0

Persons Killed

34

-8.1%was 37

Persons Injured

6

200.0%was 2

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. 5 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Peabody increased year-over-year, with 131 crashes in June 2023 compared to 113 in June 2022. This represents a 15.93% rise in total crash incidents for the month.

6

Hit-and-Run Crashes — June 2023

200.0% vs prior (2)

Hit-and-run crashes increased substantially from 2 in June 2022 to 6 in June 2023, marking a 200% increase. The hit-and-run rate also rose from 1.8% of total crashes in June 2022 to 4.6% in June 2023, indicating an upward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 0%

33

Motorists Injured

Prior: 34-2.9%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Thursday in June 2022 (21 crashes) to Saturday in June 2023 (24 crashes). The peak crash hour also moved from 8 AM in June 2022 (12 crashes) to 4 PM in June 2023 (13 crashes), indicating a shift in crash concentration towards later in the day.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes reported in either June 2023 or June 2022. Total injuries decreased by 3, from 37 injured persons in June 2022 to 34 injured persons in June 2023. In terms of crash severity, June 2023 saw 1 serious injury crash, which was not present in June 2022, while minor injury crashes decreased from 17 to 14.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes0.8%
Minor Injury14minor injury crashes10.7%
-17.6%prior 17
Possible Injury9possible injury crashes6.9%
0.0%prior 9
No Injury102no injury crashes77.9%
22.9%prior 83

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'No improper driving,' increased by 9 crashes, from 32 in June 2022 to 41 in June 2023. 'Inattention' crashes decreased by 6, from 26 to 20, while 'Followed too closely' crashes increased by 4, from 12 to 16. 'Other improper action' saw a substantial increase of 7 crashes, rising from 1 in June 2022 to 8 in June 2023.

Officer-Reported Primary Contributing Cause

No improper driving41 (31.3%)28.1%prior 32
Inattention20 (15.3%)-23.1%prior 26
Followed too closely16 (12.2%)33.3%prior 12
Other improper action8 (6.1%)
Failed to yield right of way6 (4.6%)-40.0%prior 10
Made an improper turn4 (3.1%)
Disregarded traffic signs, signals, road markings3 (2.3%)
Driving too fast for conditions3 (2.3%)
Failure to keep in proper lane or running off road3 (2.3%)
Visibility obstructed3 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring on wet road surfaces increased significantly, from 6 in June 2022 to 31 in June 2023, an increase of 416.67%. Concurrently, crashes during rainy weather increased from 3 to 21. Daylight crashes saw a slight increase from 101 to 105, while crashes in 'Dark - lighted roadway' conditions increased from 10 to 15.

Weather

Clear77 (59.2%)
-12.5%prior 88
Cloudy24 (18.5%)
118.2%prior 11
Rain21 (16.2%)
Cloudy/Rain3 (2.3%)
Clear/Cloudy3 (2.3%)
-57.1%prior 7
Fog, smog, smoke1 (0.8%)
Rain/Cloudy1 (0.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Weather condition at time of crash

Lighting

Daylight105 (80.8%)
4.0%prior 101
Dark - lighted roadway15 (11.5%)
50.0%prior 10
Dark - roadway not lighted4 (3.1%)
Dusk4 (3.1%)
Dawn2 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Lighting condition field

Road Surface

Dry99 (76.2%)
-7.5%prior 107
Wet31 (23.8%)
416.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 44, from 220 in June 2022 to 264 in June 2023, a 20% rise. Toyota remained the most common vehicle make involved, with its count increasing from 43 to 52. Honda saw a notable increase from 25 to 37, moving it to the second most frequent make, while Ford's involvement increased from 25 to 28.

Top Vehicle Makes (264 vehicles)

1
TOYOTA52 (19.7%)
20.9%prior 43
2
HONDA37 (14%)
48.0%prior 25
3
FORD28 (10.6%)
12.0%prior 25
4
NISSAN18 (6.8%)
12.5%prior 16
5
CHEVROLET16 (6.1%)
0.0%prior 16
6
JEEP10 (3.8%)
-16.7%prior 12
7
GMC8 (3%)
8
DODGE6 (2.3%)
9
INFI6 (2.3%)
10
KIA6 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Vehicle unit records

20 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (287 persons with recorded sex)

Male164 (57.1%)
43.9%prior 114
Female123 (42.9%)
1.7%prior 121

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 25 mph speed zones increased from 31 in June 2022 to 40 in June 2023, representing a 29.03% rise. Crashes in 30 mph zones also increased significantly, from 15 to 22. Conversely, crashes in 35 mph zones saw a decrease from 12 to 4, and 55 mph zones decreased from 13 to 11.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · 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: 2023-06-01 through 2023-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-06-01 through 2023-06-30 (30 days)
  • Geographic scope: PEABODY, MA
  • Total crash records analyzed: 131
  • Total persons involved: 310
  • Total vehicles involved: 264

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: June 2023." Published June 21, 2026. Reporting period: 2023-06-01 to 2023-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/peabody/june-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

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Peabody, MA Crash Report — June 2023 | ThatCarHitMe.com