ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MARLBOROUGH, MA · AUGUST 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/august-2024-report
Monthly Traffic Safety Analysis
104 CRASHES IN
MARLBOROUGH, MA
AUGUST 2024
Total crashes in Marlborough for August 2024 were 104, an increase from 75 crashes in August 2023. This represents a 38.67% rise in total crashes year-over-year. The most notable shift was the significant increase in crashes attributed to "Failed to yield right of way," which more than doubled from 4 to 12 incidents.
104
▲ 38.7%was 75
Total Crash Events
0
Persons Killed
26
▲ 44.4%was 18
Persons Injured
12
▲ 33.3%was 9
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. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for Marlborough in August 2024 indicates a rising trend compared to August 2023. Total crashes increased by 38.67%, from 75 to 104. Correspondingly, total injuries also rose by 44.44%, from 18 to 26.
12
Hit-and-Run Crashes — August 2024
▲ 33.3% vs prior (9)
The number of hit-and-run crashes increased from 9 in August 2023 to 12 in August 2024. Despite this increase in count, the overall hit-and-run rate slightly decreased from 12% of total crashes in the prior period to 11.5% in the current period.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
25
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns for crashes showed shifts in peak times year-over-year. In August 2024, the peak day for crashes was Thursday with 19 incidents, whereas in August 2023, the peak day was Wednesday with 15 incidents. The peak crash hour also shifted from 3 p.m. with 9 crashes in the prior period to 6 p.m. with 12 crashes in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities remained at zero in both August 2023 and August 2024. However, serious injuries increased from 1 (1.3% of crashes) in the prior period to 2 (1.9% of crashes) in the current period. Minor injuries decreased from 12 to 10, while possible injuries increased from 2 to 5 year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Most severe injury per crash record
Top Contributing Factors
Several contributing factors saw notable increases in crash counts. "Failed to yield right of way" crashes increased from 4 to 12, marking a 200% rise in count. "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" also saw a substantial increase from 1 to 6 incidents. "Inattention" and "Followed too closely" remained prominent factors, with counts rising from 17 to 20 and 9 to 13, respectively.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 65 to 82, mirroring the overall rise in total crashes. Crashes in daylight conditions also increased from 60 to 81 year-over-year. Similarly, crashes on dry road surfaces rose from 66 to 93, and on wet surfaces from 8 to 10.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Road surface condition field
Vehicles & Demographics
Toyota and Honda maintained their positions as the top two vehicle makes involved in crashes, with Toyota increasing from 23 to 36 and Honda from 17 to 26. Ford replaced Chevrolet in the top three, increasing from 9 to 24 vehicles. The age group 26-34 experienced a significant increase in persons involved in crashes, rising from 22 to 55, while the 65+ age group also saw an increase from 12 to 20.
Top Vehicle Makes (196 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Vehicle unit records
29 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (204 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · Person-level records linked to crash events
Speed Limit Zones
The highest number of crashes in both periods occurred in 30 mph zones, increasing from 20 crashes in August 2023 to 38 crashes in August 2024. Crashes in 65 mph zones decreased from 16 to 14, while crashes in 25 mph zones increased from 11 to 14. No fatalities were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-08-01 to 2024-08-31 · 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: 2024-08-01 through 2024-08-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-08-01 through 2024-08-31 (31 days)
- Geographic scope: MARLBOROUGH, MA
- Total crash records analyzed: 104
- Total persons involved: 234
- Total vehicles involved: 196
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: August 2024." Published June 21, 2026. Reporting period: 2024-08-01 to 2024-08-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/marlborough/august-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: 2024-08-01 – 2024-08-31
Generated: June 21, 2026 · All rights reserved