Monthly Traffic Safety Analysis

38 CRASHES IN
WAKEFIELD, MA
APRIL 2023

All metrics benchmarked againstApril 2022

In April 2023, Wakefield experienced 38 total crashes, a 58.3% increase from the 24 crashes reported in April 2022. This period also saw the emergence of hit-and-run incidents, which increased from 0 crashes in the prior period to 4 crashes in the current period.

38

58.3%was 24

Total Crash Events

0

Persons Killed

7

-36.4%was 11

Persons Injured

4

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 · 2023-04-01 to 2023-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a significant increase in crash incidents, with total crashes rising from 24 in April 2022 to 38 in April 2023. This represents a 58.3% increase in crashes year-over-year.

4

Hit-and-Run Crashes — April 2023

10.5% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 0%

6

Motorists Injured

Prior: 11-45.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · 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 Friday with 8 incidents in April 2022 to Saturday with 10 incidents in April 2023. The peak hour for crashes also shifted, moving from 5 PM with 5 incidents in the prior period to 4 PM with 5 incidents in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

No fatal crashes occurred in either period. Total injuries decreased from 11 in April 2022 to 7 in April 2023. The proportion of crashes resulting in no injury increased from 70.8% in the prior period to 78.9% in the current period, while minor injury crashes decreased from 20.8% to 10.5%.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.6%
Minor Injury4minor injury crashes10.5%
-20.0%prior 5
Possible Injury2possible injury crashes5.3%
0.0%prior 2
No Injury30no injury crashes78.9%
76.5%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor shifted from 'Failed to yield right of way' (5 crashes) in April 2022 to 'No improper driving' (10 crashes) in April 2023. 'No improper driving' crashes increased by 400% in count, while 'Failed to yield right of way' crashes increased by 60% to 8. Factors like 'Followed too closely' and 'Inattention' both doubled in count, from 3 crashes each in the prior period to 6 crashes each in the current period.

Officer-Reported Primary Contributing Cause

No improper driving10 (26.3%)
Failed to yield right of way8 (21.1%)60.0%prior 5
Followed too closely6 (15.8%)
Inattention6 (15.8%)
Other improper action3 (7.9%)
Distracted1 (2.6%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in clear weather conditions increased from 16 in April 2022 to 28 in April 2023, while crashes on dry road surfaces increased from 21 to 34. Crashes in daylight conditions also rose from 20 to 27. There was a slight increase in crashes under wet road conditions, from 3 to 4.

Weather

Clear28 (73.7%)
75.0%prior 16
Cloudy6 (15.8%)
20.0%prior 5
Rain3 (7.9%)
Clear/Cloudy1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Weather condition at time of crash

Lighting

Daylight27 (73.0%)
35.0%prior 20
Dark - lighted roadway6 (16.2%)
Dark - roadway not lighted3 (8.1%)
Dawn1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Lighting condition field

Road Surface

Dry34 (89.5%)
61.9%prior 21
Wet4 (10.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (73 vehicles)

1
TOYOTA9 (12.3%)
50.0%prior 6
2
JEEP8 (11%)
3
FORD8 (11%)
4
HONDA8 (11%)
33.3%prior 6
5
CHEVROLET5 (6.8%)
6
NISSAN4 (5.5%)
7
SUBARU4 (5.5%)
8
LEXUS3 (4.1%)
9
BUIC2 (2.7%)
10
MERCEDES-BENZ2 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Vehicle unit records

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

Sex Distribution (74 persons with recorded sex)

Male42 (56.8%)
68.0%prior 25
Female32 (43.2%)
14.3%prior 28

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Person-level records linked to crash events

Speed Limit Zones

No fatal crashes were recorded in any speed zone during either period. Crashes in the 30 mph zone increased from 11 in April 2022 to 16 in April 2023, and those in the 55 mph zone increased from 8 to 11. While the 15 mph zone had 1 crash in the prior period but none in the current, the 65 mph speed zone appeared in the current period with 2 crashes, having no recorded crashes in the prior period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · 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: 2023-04-01 through 2023-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-04-01 through 2023-04-30 (30 days)
  • Geographic scope: WAKEFIELD, MA
  • Total crash records analyzed: 38
  • Total persons involved: 84
  • Total vehicles involved: 73

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: April 2023." Published June 21, 2026. Reporting period: 2023-04-01 to 2023-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wakefield/april-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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Wakefield, MA Crash Report — April 2023 | ThatCarHitMe.com