ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MARLBOROUGH, MA · JUNE 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/june-2024-report
Monthly Traffic Safety Analysis
118 CRASHES IN
MARLBOROUGH, MA
JUNE 2024
In June 2024, Marlborough experienced 118 crashes, an increase of 9.26% compared to the 108 crashes reported in June 2023. Despite the rise in overall crash incidents, total injuries decreased by 14.81%, falling from 27 to 23. A notable shift was the increase in "Inattention" as the leading contributing factor, rising from 18 to 26 crashes.
118
▲ 9.3%was 108
Total Crash Events
0
Persons Killed
23
▼ -14.8%was 27
Persons Injured
13
▲ 8.3%was 12
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. 6 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in Marlborough show an upward trend, with total crashes increasing by 9.26% from 108 in June 2023 to 118 in June 2024. Conversely, the number of total injuries decreased by 14.81% year-over-year, from 27 to 23. Fatalities remained at zero for both periods.
13
Hit-and-Run Crashes — June 2024
▲ 8.3% vs prior (12)
The number of hit-and-run crashes increased slightly from 12 in June 2023 to 13 in June 2024. Despite this increase in count, the hit-and-run rate remained relatively stable, showing a minor decrease from 11.1% to 11%. This indicates that the proportion of crashes involving a hit-and-run incident was largely consistent year-over-year.
Vulnerable Road User Casualties
0
Motorists Killed
23
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes shifted year-over-year, with the peak crash day moving from Friday in June 2023 (25 crashes) to Thursday in June 2024 (23 crashes). The peak crash hour also changed, occurring at 1 PM with 12 crashes in June 2024, compared to 2 PM with 17 crashes in June 2023. Notably, crashes on Fridays decreased significantly from 25 to 12, while crashes on Thursdays increased from 15 to 23.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While fatal crashes remained at zero for both periods, the total number of injuries decreased from 27 in June 2023 to 23 in June 2024. The number of serious injury crashes (1) and minor injury crashes (11) remained consistent year-over-year. However, possible injury crashes increased from 4 in June 2023 to 7 in June 2024, representing a rise in their proportion of total crashes from 3.7% to 5.9%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Most severe injury per crash record
Top Contributing Factors
The top contributing factors saw a shift in ranking and count year-over-year. "Inattention" became the leading factor in June 2024 with 26 crashes, up from 18 crashes in June 2023. Conversely, "No improper driving" decreased from 29 crashes to 22 crashes, and "Followed too closely" saw a reduction from 19 crashes to 17 crashes. "Failed to yield right of way" also decreased from 11 crashes to 6 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 80 in June 2023 to 93 in June 2024, while crashes during rainy conditions decreased from 11 to 6. Similarly, crashes on dry road surfaces rose from 87 to 106, and those on wet surfaces decreased from 19 to 11. The number of crashes occurring during daylight hours also increased from 86 to 92, while crashes during dusk decreased from 6 to 2.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Road surface condition field
Vehicles & Demographics
The distribution of persons involved in crashes showed shifts across several age groups. The 0-15 age group saw a decrease from 52 to 40 persons, while the 16-20 age group increased from 29 to 38 persons. The 35-44 age group also experienced a notable increase from 23 to 40 persons involved. Among vehicle makes, TOYOTA remained the most common, increasing its count from 36 to 49, while HONDA vehicles involved decreased from 31 to 23.
Top Vehicle Makes (226 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Vehicle unit records
31 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (247 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph zones increased from 13 to 21, and those in 30 mph zones rose from 23 to 32 year-over-year. Crashes in 65 mph zones also saw an increase, from 19 to 23. Conversely, crashes in 35 mph zones decreased from 23 to 18, and in 40 mph zones from 15 to 13. A crash in a 50 mph zone was reported in June 2024, where none were recorded in June 2023.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · 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: 2024-06-01 through 2024-06-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-06-01 through 2024-06-30 (30 days)
- Geographic scope: MARLBOROUGH, MA
- Total crash records analyzed: 118
- Total persons involved: 287
- Total vehicles involved: 226
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: June 2024." Published June 21, 2026. Reporting period: 2024-06-01 to 2024-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/marlborough/june-2024-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: 2024-06-01 – 2024-06-30
Generated: June 21, 2026 · All rights reserved