Monthly Traffic Safety Analysis

41 CRASHES IN
WAKEFIELD, MA
OCTOBER 2023

All metrics benchmarked againstOctober 2022

In October 2023, Wakefield experienced 41 total crashes, an increase of 13.9% compared to the 36 crashes reported in October 2022. The most significant year-over-year shift was the increase in total fatalities from 0 in October 2022 to 1 in October 2023.

41

13.9%was 36

Total Crash Events

1

Persons Killed

13

62.5%was 8

Persons Injured

7

600.0%was 1

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in Wakefield increased year-over-year, rising from 36 crashes in October 2022 to 41 crashes in October 2023. This represents a 13.9% increase in total crash incidents.

7

Hit-and-Run Crashes — October 2023

600.0% vs prior (1)

Hit-and-run crashes increased significantly year-over-year, rising from 1 in October 2022 to 7 in October 2023. This caused the hit-and-run rate to trend sharply upward, from 2.8% to 17.1% of all crashes.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

1

Pedestrians Injured

Prior: 0%

12

Motorists Injured

Prior: 850.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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 Sunday (9 crashes) in October 2022 to Monday (10 crashes) in October 2023. The peak crash hour also changed, moving from 5 p.m. with 7 crashes in October 2022 to 12 p.m. with 5 crashes in October 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Total fatalities increased from 0 in October 2022 to 1 in October 2023, resulting in a fatal crash rate of 2.44% in the current period compared to 0% prior. Total injuries also rose from 8 to 13 year-over-year. Minor injury crashes increased from 5 (13.9% share) to 9 (22% share), while possible injury crashes decreased from 2 (5.6% share) to 1 (2.4% share).

Outcome by Severity (Crash Events)

Fatal1fatal crashes2.4%
Minor Injury9minor injury crashes22%
80.0%prior 5
Possible Injury1possible injury crashes2.4%
-50.0%prior 2
No Injury26no injury crashes63.4%
-3.7%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Inattention' crashes doubled from 3 to 6, and 'Failed to yield right of way' crashes increased by 150%, from 2 to 5. Conversely, crashes attributed to 'Followed too closely' decreased by 60%, from 5 crashes in October 2022 to 2 crashes in October 2023. 'No improper driving' crashes increased from 8 to 10.

Officer-Reported Primary Contributing Cause

No improper driving10 (24.4%)25.0%prior 8
Inattention6 (14.6%)
Failed to yield right of way5 (12.2%)
Followed too closely2 (4.9%)-60.0%prior 5
Glare2 (4.9%)
Distracted2 (4.9%)
Failure to keep in proper lane or running off road2 (4.9%)
Made an improper turn2 (4.9%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (2.4%)
Physical impairment1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 26 to 27, while those in rainy conditions doubled from 2 to 4. Crashes during daylight hours increased from 23 to 28, and crashes on dry road surfaces increased from 28 to 32.

Weather

Clear27 (65.9%)
3.8%prior 26
Cloudy6 (14.6%)
Rain4 (9.8%)
Clear/Other1 (2.4%)
Clear/Clear1 (2.4%)
Cloudy/Rain1 (2.4%)
Rain/Cloudy1 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash

Lighting

Daylight28 (70.0%)
21.7%prior 23
Dark - lighted roadway8 (20.0%)
-27.3%prior 11
Dark - unknown roadway lighting1 (2.5%)
Dusk1 (2.5%)
Dawn1 (2.5%)
Dark - roadway not lighted1 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field

Road Surface

Dry32 (78.0%)
14.3%prior 28
Wet9 (22.0%)
28.6%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 69 to 82, an 18.8% rise year-over-year. Among top makes, TOYOTA saw the largest increase in involvement, rising from 7 to 13 vehicles, while HONDA vehicles increased from 13 to 16. The 45-54 age group showed a notable increase in persons involved, rising from 10 to 15, and the 55-64 age group more than doubled from 4 to 9 persons.

Top Vehicle Makes (82 vehicles)

1
HONDA16 (19.5%)
23.1%prior 13
2
TOYOTA13 (15.9%)
85.7%prior 7
3
FORD11 (13.4%)
0.0%prior 11
4
CADI5 (6.1%)
5
SUBARU4 (4.9%)
6
NISSAN3 (3.7%)
-40.0%prior 5
7
MAZDA2 (2.4%)
8
CHRYSLER2 (2.4%)
9
MERCEDES-BENZ2 (2.4%)
10
LINC1 (1.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records

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

Sex Distribution (75 persons with recorded sex)

Male38 (50.7%)
-11.6%prior 43
Female37 (49.3%)
32.1%prior 28

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph speed zones increased slightly from 21 to 22, with one fatal crash occurring in this zone in October 2023, compared to zero in October 2022. Crashes in 55 mph speed zones increased from 9 to 11, with no fatalities reported in either period for this zone.

Fatal crashes by zone: 30 mph: 1 of 22 (4.545%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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: 2023-10-01 through 2023-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-10-01 through 2023-10-31 (31 days)
  • Geographic scope: WAKEFIELD, MA
  • Total crash records analyzed: 41
  • Total persons involved: 97
  • Total vehicles involved: 82

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: October 2023." Published June 21, 2026. Reporting period: 2023-10-01 to 2023-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wakefield/october-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 — October 2023 | ThatCarHitMe.com