ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WAKEFIELD, MA · JANUARY 2025
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/wakefield/january-2025-report
Monthly Traffic Safety Analysis
48 CRASHES IN
WAKEFIELD, MA
JANUARY 2025
In January 2025, Wakefield experienced 48 total crashes, marking a 26.3% increase compared to the 38 crashes recorded in January 2024. A significant shift was the occurrence of one fatality in the current period, whereas no fatalities were reported in the prior year.
48
▲ 26.3%was 38
Total Crash Events
1
Persons Killed
12
▼ -7.7%was 13
Persons Injured
4
▲ 33.3%was 3
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. 3 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 2025-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for Wakefield indicates an upward trend, with total crashes increasing by 26.3% from 38 in January 2024 to 48 in January 2025. This represents a notable rise in crash incidents year-over-year.
4
Hit-and-Run Crashes — January 2025
▲ 33.3% vs prior (3)
Hit-and-run incidents increased in January 2025, with 4 crashes reported compared to 3 in January 2024, representing a 33.3% rise in count. The hit-and-run rate also saw a slight increase, moving from 7.9% in the prior period to 8.3% in the current period.
Vulnerable Road User Casualties
1
Motorists Killed
12
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes shifted year-over-year. In January 2025, crashes peaked on Mondays and Wednesdays with 10 incidents each, a change from January 2024 where Saturdays saw the highest count at 8 crashes. The peak crash hour remained consistent at 5 crashes, occurring at 4 PM in the prior period and 6 PM in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
A critical change in crash severity was the increase in total fatalities from zero in January 2024 to one in January 2025. Conversely, total injuries decreased slightly from 13 to 12, representing a 7.7% reduction. The proportion of serious injury crashes increased from 2.6% to 4.2%, while minor injury crashes decreased from 18.4% to 10.4%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Most severe injury per crash record
Top Contributing Factors
Contributing factors saw notable shifts, with 'Inattention' crashes increasing significantly from 2 in January 2024 to 10 in January 2025, a 400% rise in count. Crashes attributed to 'Failed to yield right of way' decreased by 20% from 5 to 4, while 'No improper driving' and 'Followed too closely' remained consistent with 8 and 4 crashes respectively. 'Disregarded traffic signs, signals, road markings' emerged as a top factor in the current period with 5 crashes, not being a top factor in the prior period.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions show shifts, with incidents occurring in 'Clear' weather increasing from 23 to 37, while 'Rain' conditions saw a decrease from 2 to 1. Crashes on 'Dry' road surfaces rose from 21 to 35, whereas those on 'Wet' surfaces decreased from 9 to 5. Incidents during 'Daylight' hours increased from 21 to 30, with 'Dark - lighted roadway' incidents remaining at 13.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 35.3%, from 68 in January 2024 to 92 in January 2025. There was a notable increase in persons aged 0-15 (from 6 to 12) and 55-64 (from 7 to 16) involved in crashes. Honda and Toyota remained among the top vehicle makes involved, with both seeing an increase in their counts from 10 to 14 and 9 to 14 respectively.
Top Vehicle Makes (92 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Vehicle unit records
10 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (102 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed limit zone significantly increased from 20 in January 2024 to 32 in January 2025, marking a 60% rise, and included one fatal crash in the current period compared to none prior. Conversely, crashes in the 55 mph zone decreased by 27.3%, from 11 to 8. The 10 mph and 65 mph zones maintained consistent crash counts year-over-year.
Fatal crashes by zone: 30 mph: 1 of 32 (3.125%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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 2025-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-01-31 (31 days)
- Geographic scope: WAKEFIELD, MA
- Total crash records analyzed: 48
- Total persons involved: 115
- Total vehicles involved: 92
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: January 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wakefield/january-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-01-01 – 2025-01-31
Generated: June 21, 2026 · All rights reserved