ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MARLBOROUGH, 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/marlborough/2025-annual-report
Yearly Traffic Safety Analysis
1,064 CRASHES IN
MARLBOROUGH, MA
2025
In 2025, Marlborough recorded 1,064 traffic crashes, a 16.6% decrease from the 1,275 crashes reported in 2024. While overall crashes declined, the number of reported injuries increased by 7.0%, from 244 to 261. Fatalities also decreased from two in the prior period to one in the current period.
1,064
▼ -16.5%was 1,275
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
261
▲ 7.0%was 244
Persons Injured
96
▼ -23.8%was 126
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. 33 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 Marlborough saw a significant year-over-year decline, falling by 16.6% from 1,275 in 2024 to 1,064 in 2025. Despite the reduction in total collisions, the number of people injured rose by 7.0% from 244 to 261. The number of fatalities decreased from two to one over the same period.
96
Hit-and-Run Crashes — 2025
▼ -23.8% vs prior (126)
The number of hit-and-run incidents decreased from 126 in 2024 to 96 in 2025, a 23.8% reduction in count. The hit-and-run rate, which measures the percentage of total crashes that were hit-and-runs, also trended downward. This rate fell from 9.9% in the prior year to 9.0% in the current year, indicating a modest decline in the prevalence of these events relative to all crashes.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
11
Pedestrians Injured
4
Cyclists Injured
245
Motorists Injured
1
Other 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 shifted between the two periods. The peak day for crashes moved from Thursday (207 crashes) in 2024 to Tuesday (166 crashes) in 2025. Similarly, the peak hour for collisions shifted an hour earlier, from 5 p.m. (118 crashes) in the prior year to 4 p.m. (102 crashes) in the current year. Weekday crash distribution in 2025 was more uniform compared to the distinct Thursday peak observed 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 fatal crash rate decreased from 0.16% in 2024 to 0.09% in 2025, with one fatal crash recorded compared to two in the prior year. While the total number of crashes fell, the proportion of crashes involving an injury increased. Crashes resulting in serious, minor, or possible injury collectively accounted for 18.7% of all incidents in 2025, up from a 15.4% share in 2024. Correspondingly, the share of no-injury crashes declined from 80.6% to 78.1%.
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 top three reported contributing factors remained consistent year-over-year: Inattention, Following too closely, and Failure to yield right of way. However, the count for 'Inattention' as a factor decreased significantly by 30.6%, from 229 incidents in 2024 to 159 in 2025. Conversely, the count of crashes attributed to 'Followed too closely' increased by 14.0% (from 129 to 147), and 'Failed to yield right of way' saw a slight increase of 2.8% in its incident count (from 107 to 110).
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 environmental conditions under which crashes occurred showed some shifts year-over-year. The proportion of crashes happening during daylight hours increased from 65.8% in 2024 to 69.9% in 2025. Correspondingly, the share of crashes in dark conditions (lighted or unlighted) decreased from 27.8% to 23.7%. The distribution of crashes by weather and road surface conditions remained relatively stable, with incidents on dry roads during clear weather constituting the majority in both periods.
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
The top three vehicle makes involved in crashes remained Toyota, Honda, and Ford in both 2024 and 2025, with each showing a decrease in total count consistent with the overall drop in collisions. Analysis of the age distribution of all persons involved in crashes shows a largely stable demographic profile between the two years. The proportional representation of most age groups saw minimal change, with the 16-20 age group's share decreasing slightly from 10.0% to 9.3%, while the 65+ age group's share saw a small increase from 8.7% to 9.0%.
Top Vehicle Makes (2,023 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
239 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,151 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 different speed zones saw a minor shift, with a slightly larger proportion of incidents occurring in zones with posted limits of 30 mph or less (59.9% in 2025 vs. 56.9% in 2024). In 2025, the year's single fatal crash occurred in a 40 mph zone. This contrasts with the prior year, where both fatal crashes took place in a 50 mph zone.
Fatal crashes by zone: 40 mph: 1 of 119 (0.84%)
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: MARLBOROUGH, MA
- Total crash records analyzed: 1,064
- Total persons involved: 2,409
- Total vehicles involved: 2,023
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: 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/marlborough/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