Yearly Traffic Safety Analysis

417 CRASHES IN
WAKEFIELD, MA
2025

All metrics benchmarked against2024

In 2025, Wakefield recorded 417 total traffic crashes, a 14% decrease from the 485 crashes reported in 2024. While overall crashes and injuries declined, the number of hit-and-run incidents increased from 42 in the prior period to 57 in the current period.

417

▼ -14.0%was 485

Total Crash Events

▼ -50.0%was 2

Persons Killed

125

▼ -10.1%was 139

Persons Injured

▲ 35.7%was 42

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, traffic safety trends in Wakefield improved year-over-year. Total crashes fell by 14%, from 485 in 2024 to 417 in 2025. This downward trend was also reflected in personal harm, with total injuries decreasing by 10.1% (from 139 to 125) and fatalities dropping from 2 to 1.

Hit-and-Run Crashes — 2025

▲ 35.7% vs prior (42)

The incidence of hit-and-run crashes in Wakefield showed a significant upward trend. The total number of hit-and-run events increased by 35.7%, from 42 in 2024 to 57 in 2025. The hit-and-run rate, which measures these incidents as a percentage of all crashes, also rose sharply from 8.7% in the prior period to 13.7% in the current period.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 1↓-100.0%

Cyclists Killed

Prior: 0→0.0%

Motorists Killed

Prior: 1→0.0%

Other Killed

Prior: 0→0.0%

Pedestrians Injured

Prior: 6↓-33.3%

Cyclists Injured

Prior: 7↓-14.3%

114

Motorists Injured

Prior: 123↓-7.3%

Other Injured

Prior: 3↓-66.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes in Wakefield remained consistent year-over-year, though the volume of incidents decreased. Friday continued to be the peak day for crashes in both 2025 (66 crashes) and 2024 (92 crashes). Similarly, the 5 PM hour was the most frequent time for crashes in both periods, with 36 incidents in 2025 compared to 53 in 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The number of fatal crashes decreased from 2 in 2024 to 1 in 2025, with the fatal crash rate dropping from 0.41 to 0.24 per 100 crashes. The proportion of crashes resulting in minor or possible injuries increased, with minor injury crashes accounting for 17.5% of all incidents in 2025, up from a 14.8% share in 2024. Correspondingly, the share of crashes with no reported injuries decreased from 74.8% in the prior period to 70.7% in the current period.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.2%

↓-50.0%prior 2

Serious Injury8serious injury crashes1.9%

↓-11.1%prior 9

Minor Injury73minor injury crashes17.5%

↑1.4%prior 72

Possible Injury20possible injury crashes4.8%

→0.0%prior 20

No Injury295no injury crashes70.7%

↓-18.7%prior 363

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

While 'No improper driving' remained the most common finding in both periods, its count slightly decreased from 127 to 121. The most notable shift in driver behaviors was the increase in crashes attributed to 'Followed too closely,' which rose from 51 to 59 incidents, becoming the second-most cited factor in 2025. Conversely, crashes involving 'Inattention' decreased by 28% (from 61 to 44 incidents), and 'Failed to yield right of way' dropped by 33% (from 49 to 33 incidents). Crashes involving an 'erratic, reckless, careless, negligent or aggressive manner' more than doubled, increasing from 10 to 22 incidents.

Officer-Reported Primary Contributing Cause

No improper driving121 (29%)↓-4.7%prior 127

Followed too closely59 (14.1%)↑15.7%prior 51

Inattention44 (10.6%)↓-27.9%prior 61

Failed to yield right of way33 (7.9%)↓-32.7%prior 49

Operating vehicle in erratic, reckless, careless, negligent or aggressive manner22 (5.3%)↑120.0%prior 10

Disregarded traffic signs, signals, road markings19 (4.6%)↑90.0%prior 10

Failure to keep in proper lane or running off road17 (4.1%)↓-22.7%prior 22

Distracted10 (2.4%)↑11.1%prior 9

Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway10 (2.4%)↓-16.7%prior 12

Operating defective equipment6 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both periods occurred in clear weather and on dry roads, with proportions remaining stable year-over-year. In 2025, 82.3% of crashes happened on dry surfaces, compared to 83.7% in 2024. A more noticeable shift occurred in lighting conditions; crashes during daylight hours constituted a larger share of the total in 2025 (73.6%) compared to 2024 (70.1%). Correspondingly, the proportion of crashes on dark, lighted roadways decreased from 22.1% of all incidents in 2024 to 16.3% in 2025.

Weather

Clear278 (67.3%)

↓-21.7%prior 355

Clear/Clear55 (13.3%)

↑139.1%prior 23

Rain23 (5.6%)

→0.0%prior 23

Cloudy20 (4.8%)

↓-53.5%prior 43

Rain/Rain7 (1.7%)

Clear/Cloudy7 (1.7%)

Snow5 (1.2%)

↓-50.0%prior 10

Cloudy/Rain4 (1.0%)

↓-55.6%prior 9

Sleet, hail (freezing rain or drizzle)4 (1.0%)

Cloudy/Cloudy3 (0.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight307 (74.3%)

↓-9.7%prior 340

Dark - lighted roadway68 (16.5%)

↓-36.4%prior 107

Dark - roadway not lighted16 (3.9%)

↑23.1%prior 13

Dusk15 (3.6%)

↓-6.3%prior 16

Dawn6 (1.5%)

Dark - unknown roadway lighting1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry343 (83.1%)

↓-15.5%prior 406

Wet51 (12.3%)

↓-8.9%prior 56

Snow10 (2.4%)

↓-28.6%prior 14

Ice6 (1.5%)

Sand, mud, dirt, oil, gravel1 (0.2%)

Slush1 (0.2%)

Water (standing, moving)1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The demographic profile of persons involved in crashes remained largely consistent, with no significant shifts in the proportional representation of any age group. The total number of vehicles involved in crashes decreased from 942 in 2024 to 823 in 2025. While Toyota was the most common make in crashes in 2024 (135 vehicles), Honda took the top spot in 2025 with 111 vehicles involved. The top five vehicle makes involved in crashes were the same across both years: Honda, Toyota, Ford, Chevrolet, and Nissan.

Top Vehicle Makes (823 vehicles)

HONDA111 (13.5%)

↓-4.3%prior 116

TOYOTA110 (13.4%)

↓-18.5%prior 135

FORD76 (9.2%)

↓-16.5%prior 91

NISSAN61 (7.4%)

↑52.5%prior 40

CHEVROLET53 (6.4%)

↓-15.9%prior 63

SUBARU36 (4.4%)

↓-18.2%prior 44

JEEP35 (4.3%)

↓-31.4%prior 51

HYUNDAI23 (2.8%)

↓-20.7%prior 29

GMC20 (2.4%)

↑33.3%prior 15

KIA20 (2.4%)

↑5.3%prior 19

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (862 persons with recorded sex)

Male480 (55.7%)

↓-21.6%prior 612

Female381 (44.2%)

↓-7.3%prior 411

X / Unspecified1 (0.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes were most prevalent in 30 mph speed zones during both periods, accounting for 54.4% of incidents in 2025 and 50.1% in 2024. While the number of crashes in 55 mph zones remained proportionally stable, there was a notable decrease in incidents occurring in zones with speed limits below 30 mph, falling from 97 crashes in 2024 to 61 in 2025. All fatal crashes in both years occurred in 30 mph zones, with one fatality in 2025 and two in 2024.

Fatal crashes by zone: 30 mph: 1 of 227 (0.441%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
Report generated: June 21, 2026

Data Coverage

Reporting period: 2025-01-01 through 2025-12-31 (365 days)
Geographic scope: WAKEFIELD, MA
Total crash records analyzed: 417
Total persons involved: 1,007
Total vehicles involved: 823

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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wakefield/2025-annual-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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417 CRASHES INWAKEFIELD, MA2025