Monthly Traffic Safety Analysis

24 CRASHES IN
WAKEFIELD, MA
JUNE 2022

All metrics benchmarked againstJune 2021

In June 2022, Wakefield experienced 24 total crashes, a decrease from the 39 crashes reported in June 2021. This represents a 38.5% reduction in total crashes year-over-year. The most notable shift was a significant 75% decrease in total injuries, falling from 8 in the prior period to 2 in the current period.

24

-38.5%was 39

Total Crash Events

0

Persons Killed

2

-75.0%was 8

Persons Injured

4

33.3%was 3

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data indicates a downward trend in Wakefield for June 2022 compared to June 2021. Total crashes decreased by 15, from 39 to 24, marking a 38.5% reduction. Similarly, total injuries saw a substantial decline of 6, from 8 to 2, representing a 75% decrease year-over-year.

4

Hit-and-Run Crashes — June 2022

33.3% vs prior (3)

Hit-and-run crashes increased from 3 in June 2021 to 4 in June 2022, representing a 33.3% increase in count. The hit-and-run rate also rose from 7.7% of total crashes in the prior period to 16.7% in the current period, indicating an upward trend in their occurrence relative to total incidents.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 7-71.4%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns for crashes shifted between the two periods. The peak day for crashes moved from Thursday in June 2021, with 7 incidents, to Friday in June 2022, with 8 incidents. The peak hour also shifted from 4 PM in the prior year to 2 PM in the current year, with both hours recording 6 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The distribution of crash severity changed year-over-year, with a notable reduction in injury crashes. Minor injury crashes decreased from 4 in June 2021 to 1 in June 2022, while possible injury crashes also decreased from 2 to 1. The proportion of crashes resulting in no injury increased from 76.9% to 91.7%, reflecting the overall decrease in injury incidents.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes4.2%
-75.0%prior 4
Possible Injury1possible injury crashes4.2%
-50.0%prior 2
No Injury22no injury crashes91.7%
-26.7%prior 30

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'No improper driving' crashes increased from 9 in June 2021 to 12 in June 2022, a 33.3% increase in count, and its share of crashes rose from 23.1% to 50%. Conversely, 'Followed too closely' crashes decreased significantly from 6 to 1, an 83.3% reduction in count. 'Inattention' remained constant at 4 crashes in both periods, while 'Failed to yield right of way' decreased from 3 to 1 crash.

Officer-Reported Primary Contributing Cause

No improper driving12 (50%)33.3%prior 9
Inattention4 (16.7%)
Followed too closely1 (4.2%)-83.3%prior 6
Failed to yield right of way1 (4.2%)
Over-correcting/over-steering1 (4.2%)
Visibility obstructed1 (4.2%)
Disregarded traffic signs, signals, road markings1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Regarding crash conditions, incidents occurring in 'Clear' weather decreased from 28 in June 2021 to 19 in June 2022. Crashes under 'Cloudy' conditions also saw a slight decrease from 5 to 4. For lighting conditions, crashes during 'Daylight' hours decreased from 34 to 23, and those in 'Dark - lighted roadway' conditions decreased from 2 to 1.

Weather

Clear19 (79.2%)
-32.1%prior 28
Cloudy4 (16.7%)
-20.0%prior 5
Clear/Rain1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Weather condition at time of crash

Lighting

Daylight23 (95.8%)
-32.4%prior 34
Dark - lighted roadway1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Lighting condition field

Vehicles & Demographics

Top Vehicle Makes (47 vehicles)

1
TOYOTA10 (21.3%)
11.1%prior 9
2
HONDA9 (19.1%)
0.0%prior 9
3
NISSAN6 (12.8%)
20.0%prior 5
4
CHEVROLET4 (8.5%)
-63.6%prior 11
5
FORD4 (8.5%)
-50.0%prior 8
6
JEEP2 (4.3%)
7
LEXUS2 (4.3%)
8
MACK1 (2.1%)
9
INFI1 (2.1%)
10
OTHR1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Vehicle unit records

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

Sex Distribution (58 persons with recorded sex)

Male31 (53.4%)
-11.4%prior 35
Female27 (46.6%)
-25.0%prior 36

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 30 mph speed zones decreased from 18 in June 2021 to 15 in June 2022, while crashes in 55 mph zones saw a notable reduction from 10 to 3. Conversely, crashes in 5 mph zones increased from 1 to 2, and in 25 mph zones from 1 to 2. There were no fatal crashes reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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: 2022-06-01 through 2022-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-06-01 through 2022-06-30 (30 days)
  • Geographic scope: WAKEFIELD, MA
  • Total crash records analyzed: 24
  • Total persons involved: 63
  • Total vehicles involved: 47

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). "WAKEFIELD, MA Crash Intelligence Report: June 2022." Published June 21, 2026. Reporting period: 2022-06-01 to 2022-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wakefield/june-2022-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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Wakefield, MA Crash Report — June 2022 | ThatCarHitMe.com