ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WAKEFIELD, MA · JANUARY 2026
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-2026-report
Monthly Traffic Safety Analysis
42 CRASHES IN
WAKEFIELD, MA
JANUARY 2026
Total crashes in Wakefield decreased by 12.5%, from 48 in January 2025 to 42 in January 2026. This period saw a notable reduction in severe outcomes, with fatalities dropping from 1 to 0 and total injuries decreasing from 12 to 3. Additionally, DUI-related crashes were eliminated, falling from 4 to 0.
42
▼ -12.5%was 48
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
3
▼ -75.0%was 12
Persons Injured
5
▲ 25.0%was 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. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash trends in Wakefield show a decline, with total crashes decreasing by 12.5% from 48 to 42 incidents year-over-year. This reduction is accompanied by a significant decrease in crash severity, as total fatalities fell from 1 to 0 and total injuries decreased from 12 to 3.
5
Hit-and-Run Crashes — January 2026
▲ 25.0% vs prior (4)
Hit-and-run crashes increased from 4 in January 2025 to 5 in January 2026. This represents an increase in the hit-and-run crash rate from 8.3% to 11.9% of all crashes. The number of hit-and-run incidents increased by 1 crash year-over-year.
Vulnerable Road User Casualties
0
Motorists Killed
3
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
In January 2026, crashes peaked on Tuesday and Wednesday with 8 incidents each, and the peak hour was 3 PM with 6 crashes. In January 2025, crashes peaked on Monday and Wednesday with 10 incidents each, and the peak hour was 6 PM with 5 crashes. While Wednesday remained a peak day in both periods, the peak hour for crashes shifted from 6 PM in the prior year to 3 PM in the current year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The number of fatal crashes decreased from 1 in January 2025 to 0 in January 2026. Total injuries significantly decreased from 12 in the prior period to 3 in the current period. Serious injuries (A) decreased from 2 (4.2% of crashes) to 1 (2.4% of crashes), and minor injuries (B) decreased from 5 (10.4% of crashes) to 2 (4.8% of crashes).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Most severe injury per crash record
Top Contributing Factors
In January 2026, "No improper driving" was the most frequent contributing factor with 11 crashes, an increase from 8 crashes in January 2025. "Failed to yield right of way" doubled from 4 crashes in the prior period to 8 crashes in the current period. Conversely, "Inattention" decreased from 10 crashes to 7 crashes, and "Disregarded traffic signs, signals, road markings" saw a reduction from 5 crashes to 1 crash.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
In January 2026, 27 crashes occurred in Clear weather, a decrease from 37 such crashes in January 2025. Crashes on Snow-covered roads increased from 3 in the prior period to 6 in the current period. The number of crashes occurring in Daylight decreased from 30 to 26, while crashes in Dark - lighted roadway conditions decreased from 13 to 11.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Road surface condition field
Vehicles & Demographics
Both periods show HONDA, TOYOTA, and FORD as the top three vehicle makes involved in crashes, though their counts decreased year-over-year. The total number of vehicles involved in crashes decreased from 92 in January 2025 to 83 in January 2026. Specifically, Toyota involvement decreased from 14 to 12, Honda from 14 to 12, and Ford from 12 to 9.
Top Vehicle Makes (83 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Vehicle unit records
13 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (88 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Person-level records linked to crash events
Speed Limit Zones
The 30 mph speed zone continued to account for the highest number of crashes, with 22 crashes in January 2026, down from 32 crashes in January 2025. Crashes in the 20 mph zone increased from 2 to 8. The 55 mph zone saw a decrease from 8 crashes to 3 crashes, and the only fatal crash in the prior period occurred in a 30 mph zone, with no fatal crashes reported in any speed zone in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · 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: 2026-01-01 through 2026-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2026-01-01 through 2026-01-31 (31 days)
- Geographic scope: WAKEFIELD, MA
- Total crash records analyzed: 42
- Total persons involved: 100
- Total vehicles involved: 83
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 2026." Published June 21, 2026. Reporting period: 2026-01-01 to 2026-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wakefield/january-2026-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: 2026-01-01 – 2026-01-31
Generated: June 21, 2026 · All rights reserved