ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MARLBOROUGH, MA · APRIL 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/marlborough/april-2026-report
Monthly Traffic Safety Analysis
83 CRASHES IN
MARLBOROUGH, MA
APRIL 2026
In April 2026, Marlborough experienced 83 crashes, a slight increase from the 81 crashes reported in April 2025, representing a 2.47% rise. Total fatalities remained stable at 1, and total injuries also held steady at 28. A notable shift was the complete elimination of DUI-related crashes, dropping from 2 in the prior period to 0 in the current period.
83
▲ 2.5%was 81
Total Crash Events
1
Persons Killed
28
Persons Injured
6
▼ -25.0%was 8
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash incidents in Marlborough saw a slight increase, rising from 81 crashes in April 2025 to 83 crashes in April 2026, a 2.47% year-over-year change. Despite this minor rise in total crashes, the number of fatalities remained constant at 1, and the total number of injuries also stayed the same at 28 for both periods.
6
Hit-and-Run Crashes — April 2026
▼ -25.0% vs prior (8)
Hit-and-run crashes decreased from 8 in April 2025 to 6 in April 2026, representing a 25% reduction in count. The hit-and-run rate also declined from 9.9% of all crashes in the prior period to 7.2% in the current period, indicating a downward trend.
Vulnerable Road User Casualties
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
1
Cyclists Injured
26
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Monday in April 2025, with 17 incidents, to Thursday in April 2026, which recorded 19 crashes. Similarly, the peak crash hour moved from 5 PM with 8 incidents in the prior period to 8 AM with 13 incidents in the current period. This indicates a shift in the most crash-prone times of the week and day.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The number of fatal crashes remained unchanged at 1 in both periods. However, there was a significant shift in injury severity, with serious injury crashes decreasing from 2 to 1 (a 50% reduction) and possible injury crashes dropping from 12 to 2 (an 83.3% decrease). Conversely, minor injury crashes saw a substantial increase from 5 to 19, a 280% rise year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Most severe injury per crash record
Top Contributing Factors
Contributing factors saw 'Inattention' become the leading factor, increasing from 14 crashes to 19 crashes (a 35.7% increase), while 'No improper driving' decreased by 4 crashes, from 20 to 16. 'Followed too closely' remained the third most common factor, increasing from 11 to 12 crashes (a 9.1% increase). Additionally, crashes attributed to 'Driving too fast for conditions' doubled from 2 to 4 incidents, a 100% increase.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased from 55 to 61, while those in 'Cloudy' conditions rose from 8 to 13. Crashes on 'Dry' road surfaces increased by 11, from 58 to 69, whereas crashes on 'Snow' surfaces decreased from 5 to 0. The number of crashes during 'Daylight' hours increased from 60 to 69, while incidents during 'Dawn' and 'Dusk' both decreased from 4 to 1.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved remained constant at 152 in both periods. Toyota, Honda, and Ford consistently ranked among the top vehicle makes involved, with Toyota increasing from 31 to 34, Honda from 17 to 22, and Ford from 12 to 17. The age distribution of persons involved showed an increase in the 16-20, 21-25, 26-34, 35-44, and 45-54 age groups, while the 55-64 and 65+ age groups saw decreases.
Top Vehicle Makes (152 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Vehicle unit records
14 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (177 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 65 mph speed zone increased from 7 to 13, and this zone recorded 1 fatal crash in the current period, up from 0 in the prior period. Crashes in the 5 mph zone decreased from 8 to 3, and the 25 mph zone saw a decrease from 16 to 13 incidents. Conversely, the 30 mph and 35 mph zones experienced increases in crash counts, rising from 14 to 17 and 15 to 22, respectively.
Fatal crashes by zone: 65 mph: 1 of 13 (7.692%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · 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: 2026-04-01 through 2026-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2026-04-01 through 2026-04-30 (30 days)
- Geographic scope: MARLBOROUGH, MA
- Total crash records analyzed: 83
- Total persons involved: 191
- Total vehicles involved: 152
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). "MARLBOROUGH, MA Crash Intelligence Report: April 2026." Published June 21, 2026. Reporting period: 2026-04-01 to 2026-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/marlborough/april-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: 2026-04-01 – 2026-04-30
Generated: June 21, 2026 · All rights reserved