ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WAYLAND, MA · 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/wayland/2025-annual-report
Yearly Traffic Safety Analysis
271 CRASHES IN
WAYLAND, MA
2025
In 2025, Wayland recorded 271 total vehicle crashes, a 2.7% increase from the 264 crashes recorded in 2024. While total crashes and the number of injuries (72 in 2025 vs. 75 in 2024) remained relatively stable, the most significant year-over-year change was the reduction in traffic fatalities, which dropped from one in 2024 to zero in 2025.
271
▲ 2.7%was 264
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
72
▼ -4.0%was 75
Persons Injured
8
▼ -20.0%was 10
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. 4 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 crashes in Wayland saw a slight increase, rising from 264 in 2024 to 271 in 2025, a change of 2.7%. Despite the increase in total collisions, the number of people injured decreased slightly from 75 to 72. This indicates a relatively stable trend in crash volume and outcomes year-over-year.
8
Hit-and-Run Crashes — 2025
▼ -20.0% vs prior (10)
The number of hit-and-run incidents in Wayland decreased from 10 in 2024 to 8 in 2025. This represents a downward trend in both the absolute count and the rate of occurrence. The hit-and-run rate, calculated as a percentage of total crashes, fell from 3.8% in the prior year to 3.0% in the current year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
70
Motorists Injured
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 showed some shifts between the two periods. The peak day for crashes moved from Friday (52 crashes) in 2024 to Tuesday (50 crashes) in 2025. However, the peak hour for collisions remained consistent at 3 p.m. in both years, though the number of crashes during that hour decreased from 40 in 2024 to 29 in 2025.
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
Crash severity improved in 2025, with fatal crashes decreasing from one in the prior year to zero. The proportion of crashes resulting in serious injury also saw a slight decline, from 2.3% in 2024 to 1.8% in 2025. While the count of minor injury crashes decreased from 35 to 29, the share of no-injury crashes rose slightly from 79.2% to 80.4% of all incidents.
Outcome by Severity (Crash Events)
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
The leading contributing factors shifted between the two years. While 'Inattention' remained a top cause, its count decreased by 21% from 57 crashes in 2024 to 45 in 2025. Conversely, crashes attributed to 'Followed too closely' increased by 25% in count, from 24 to 30 incidents, and those from 'Failed to yield right of way' rose by 27% in count, from 22 to 28 incidents. The most significant percentage change among top factors was a 150% increase in the count of crashes due to 'Failure to keep in proper lane or running off road,' which grew from 6 to 15 incidents.
Officer-Reported Primary Contributing Cause
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 years occurred in daylight on dry roads. In 2025, 76.8% of crashes happened during daylight, up from 72.3% in 2024. Crashes on adverse road surfaces like wet, snow, or ice made up a similar proportion of the total in both periods, accounting for 22.9% in 2025 versus 21.6% in 2024. However, there was an increase in crashes occurring during adverse weather conditions (such as cloudy, rain, or snow), which rose from 101 incidents in 2024 to 126 in 2025.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
Toyota, Honda, and Ford were the top three vehicle makes involved in crashes in both years. While Toyota remained the most common make, its involvement decreased from 85 vehicles in 2024 to 70 in 2025, while the number of Hondas involved increased from 52 to 61. Analysis of persons involved shows a significant demographic shift, with a notable increase in the 16-20 age group (from 50 to 91 persons) and the 0-15 age group (from 24 to 57 persons).
Top Vehicle Makes (490 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
27 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (585 persons with recorded sex)
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
The distribution of crashes across speed zones changed significantly year-over-year. Crashes in 35 mph zones increased from 63 in 2024 to 100 in 2025, becoming the most frequent zone for incidents. Conversely, crashes in 25 mph zones, which were the most common in the prior year, decreased from 107 to 69. The single fatal crash in 2024 occurred in a 25 mph zone, while no fatal crashes were recorded in 2025.
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: WAYLAND, MA
- Total crash records analyzed: 271
- Total persons involved: 617
- Total vehicles involved: 490
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). "WAYLAND, 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/wayland/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
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 – 2025-12-31
Generated: June 21, 2026 · All rights reserved