ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MARLBOROUGH, MA · 2024
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/2024-annual-report
Yearly Traffic Safety Analysis
1,275 CRASHES IN
MARLBOROUGH, MA
2024
In Marlborough, total crashes increased by 16.7% from 1,093 in 2023 to 1,275 in 2024. While the number of injuries decreased slightly, the most significant year-over-year change was the occurrence of two fatal crashes in 2024, compared to none in the prior year. Crashes attributed to inattention and those occurring in snowy or icy conditions saw notable increases.
1,275
▲ 16.7%was 1,093
Total Crash Events
2
Persons Killed
244
▼ -8.3%was 266
Persons Injured
126
▲ 15.6%was 109
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 48 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year data indicates a rising trend in total crashes in Marlborough, with a 16.7% increase from 1,093 incidents in 2023 to 1,275 in 2024. While total crashes rose, the number of people injured saw a slight decrease of 8.3%, from 266 to 244. However, the period saw the introduction of two fatalities, where none were recorded in the previous year.
126
Hit-and-Run Crashes — 2024
▲ 15.6% vs prior (109)
The total number of hit-and-run crashes increased from 109 in 2023 to 126 in 2024, a rise of 15.6%. However, because total crashes also increased significantly, the hit-and-run rate remained relatively stable. The rate saw a marginal decrease from 10.0% in 2023 to 9.9% in 2024, indicating that hit-and-runs did not grow disproportionately compared to other crash types.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
6
Pedestrians Injured
6
Cyclists Injured
232
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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 year-over-year. The peak day for collisions moved from Friday (177 crashes) in 2023 to Thursday (207 crashes) in 2024. Similarly, the peak hour for crashes shifted later in the day, from the 3 p.m. hour in 2023 (103 crashes) to the 5 p.m. hour in 2024 (118 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity saw a notable shift with the appearance of two fatal crashes in 2024, representing 0.2% of all incidents, compared to zero fatal crashes in 2023. The share of crashes resulting in no injuries increased from 77.6% to 80.6% year-over-year. Conversely, the proportion of crashes involving minor injuries decreased from 12.1% in 2023 to 10.2% in 2024.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The top two contributing factors, "No improper driving" and "Inattention," maintained their rankings, with their counts increasing by 18.0% and 19.3% respectively. The count of crashes where "Followed too closely" was a factor decreased by 10.4% from 144 to 129. Incidents attributed to "Driving too fast for conditions" saw a notable increase in count, rising 71.4% from 14 to 24.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The proportion of crashes occurring in clear weather and daylight conditions decreased slightly in 2024 compared to the prior year. Crashes on dry road surfaces also saw a proportional decrease, from 80.4% of all incidents in 2023 to 78.4% in 2024. Notably, incidents during adverse winter conditions increased significantly; crashes in snow more than doubled from 16 to 38, and those on icy roads increased from 6 to 27.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The top five vehicle makes involved in crashes—Toyota, Honda, Ford, Chevrolet, and Nissan—remained consistent across both years, with counts increasing for each. When examining the age distribution of persons involved, the 35-44 age group saw the most significant growth, with involvement increasing by 25.5% from 369 individuals in 2023 to 463 in 2024. The 26-34 age group also saw a notable 17.0% increase in persons involved.
Top Vehicle Makes (2,390 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
286 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,553 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes became more frequent in several lower-to-mid-range speed zones, with incidents in 30 mph zones increasing by 25.9% from 317 to 399. The two fatal crashes recorded in 2024 both occurred in a 50 mph speed zone, where no fatalities were reported in the prior year. Crashes in 65 mph zones remained unchanged, with 147 incidents reported in both 2023 and 2024.
Fatal crashes by zone: 50 mph: 2 of 17 (11.765%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: MARLBOROUGH, MA
- Total crash records analyzed: 1,275
- Total persons involved: 2,878
- Total vehicles involved: 2,390
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/marlborough/2024-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: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved