Monthly Traffic Safety Analysis

37 CRASHES IN
WAKEFIELD, MA
OCTOBER 2025

All metrics benchmarked againstOctober 2024

Total crashes in Wakefield, MA decreased by 22.9% from 48 in October 2024 to 37 in October 2025. This period saw a reduction of 11 crashes year-over-year, alongside a decrease in total injuries from 9 to 8. A notable shift occurred in contributing factors, with 'Followed too closely' becoming a more prominent factor in the current period.

37

-22.9%was 48

Total Crash Events

0

Persons Killed

8

-11.1%was 9

Persons Injured

2

-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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in Wakefield, MA showed a downward trend year-over-year, with total crashes decreasing from 48 to 37, representing a 22.9% reduction. Similarly, the total number of injuries decreased from 9 to 8, marking an 11.1% decline. Fatalities remained at zero in both periods.

2

Hit-and-Run Crashes — October 2025

-33.3% vs prior (3)

The number of hit-and-run crashes decreased from 3 in October 2024 to 2 in October 2025, representing a 33.3% decrease in count. Concurrently, the hit-and-run rate decreased from 6.3% of total crashes in the prior period to 5.4% in the current period, indicating a downward trend.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

8

Motorists Injured

Prior: 9-11.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted between the two periods. The peak day for crashes moved from Friday, with 9 crashes in October 2024, to Thursday, with 11 crashes in October 2025. The peak hour also changed significantly, from 6 p.m. (5 crashes) in the prior period to 7 a.m. (6 crashes) in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either October 2024 or October 2025. Total injuries decreased slightly from 9 to 8 year-over-year, with serious injuries decreasing from 1 to 0. However, minor injuries increased from 3 to 5, and possible injuries increased from 1 to 3, resulting in a higher proportion of crashes with minor injury (13.5% vs. 6.3%) and possible injury (8.1% vs. 2.1%) in the current period.

Outcome by Severity (Crash Events)

Minor Injury5minor injury crashes13.5%
66.7%prior 3
Possible Injury3possible injury crashes8.1%
200.0%prior 1
No Injury28no injury crashes75.7%
-31.7%prior 41

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Most severe injury per crash record

Top Contributing Factors

The distribution of contributing factors saw notable changes year-over-year. Crashes attributed to 'Followed too closely' increased by 80% in count, rising from 5 in the prior period to 9 in the current period, and became the second most frequent factor. Conversely, 'Failed to yield right of way' crashes decreased significantly by 88.9% in count, from 9 to 1, while 'Inattention' decreased by 50% in count, from 6 to 3.

Officer-Reported Primary Contributing Cause

No improper driving11 (29.7%)0.0%prior 11
Followed too closely9 (24.3%)80.0%prior 5
Inattention3 (8.1%)-50.0%prior 6
Failure to keep in proper lane or running off road2 (5.4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (5.4%)
Distracted2 (5.4%)
Visibility obstructed1 (2.7%)
Disregarded traffic signs, signals, road markings1 (2.7%)
Driving too fast for conditions1 (2.7%)
Failed to yield right of way1 (2.7%)-88.9%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring under adverse weather conditions (Rain/Rain, Rain, Cloudy, Clear/Cloudy) slightly decreased from 5 in October 2024 to 4 in October 2025. Similarly, crashes on wet or standing water road surfaces decreased from 5 to 4. A significant reduction was observed in crashes occurring in 'Dark - lighted roadway' conditions, decreasing from 15 in the prior period to 3 in the current period.

Weather

Clear22 (59.5%)
-40.5%prior 37
Clear/Clear10 (27.0%)
66.7%prior 6
Rain/Rain2 (5.4%)
Clear/Cloudy1 (2.7%)
Cloudy1 (2.7%)
Rain1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Weather condition at time of crash

Lighting

Daylight29 (78.4%)
-9.4%prior 32
Dark - lighted roadway3 (8.1%)
-80.0%prior 15
Dawn3 (8.1%)
Dark - roadway not lighted1 (2.7%)
Dusk1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Lighting condition field

Road Surface

Dry33 (89.2%)
-23.3%prior 43
Wet3 (8.1%)
Water (standing, moving)1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 96 in October 2024 to 76 in October 2025, consistent with the overall crash reduction. Toyota became the most frequently involved make, with 15 vehicles in the current period, up from 8, while Honda's involvement decreased from 14 to 7. The 45-54 and 65+ age groups saw significant decreases in persons involved, from 19 to 6 and 12 to 7 respectively, though the 16-20 age group saw a slight increase from 5 to 6.

Top Vehicle Makes (76 vehicles)

1
TOYOTA15 (19.7%)
87.5%prior 8
2
HONDA7 (9.2%)
-50.0%prior 14
3
NISSAN6 (7.9%)
4
SUBARU5 (6.6%)
5
MERCEDES-BENZ4 (5.3%)
6
LEXUS3 (3.9%)
7
CHEVROLET3 (3.9%)
-57.1%prior 7
8
GMC3 (3.9%)
9
FORD2 (2.6%)
-81.8%prior 11
10
DODGE2 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Vehicle unit records

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

Sex Distribution (73 persons with recorded sex)

Male46 (63.0%)
-25.8%prior 62
Female27 (37.0%)
-15.6%prior 32

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone decreased from 20 in the prior period to 14 in the current period. Conversely, crashes in the 55 mph speed zone increased from 12 to 16 year-over-year. All speed zones reported zero fatal crashes in both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · 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: 2025-10-01 through 2025-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-10-01 through 2025-10-31 (31 days)
  • Geographic scope: WAKEFIELD, MA
  • Total crash records analyzed: 37
  • Total persons involved: 84
  • Total vehicles involved: 76

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 2025." Published June 21, 2026. Reporting period: 2025-10-01 to 2025-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wakefield/october-2025-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 2025 | ThatCarHitMe.com