ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MARLBOROUGH, MA · SEPTEMBER 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/september-2024-report
Monthly Traffic Safety Analysis
87 CRASHES IN
MARLBOROUGH, MA
SEPTEMBER 2024
In Marlborough, total crashes increased by 7.41%, from 81 incidents in September 2023 to 87 in September 2024. Total injuries also saw an increase, rising from 17 to 19 persons injured year-over-year. A notable shift was the emergence of speeding as a contributing factor, with 4 speeding-related crashes reported in the current period compared to none in the prior period.
87
▲ 7.4%was 81
Total Crash Events
0
Persons Killed
19
▲ 11.8%was 17
Persons Injured
9
▲ 28.6%was 7
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. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash activity in Marlborough saw an upward trend year-over-year, with total crashes increasing from 81 to 87, representing a 7.41% rise. Total injuries also increased, from 17 persons injured in the prior period to 19 in the current period, an 11.76% increase. Fatalities remained at zero for both periods.
9
Hit-and-Run Crashes — September 2024
▲ 28.6% vs prior (7)
Hit-and-run incidents increased from 7 crashes in September 2023 to 9 crashes in September 2024. This represents an increase in the hit-and-run rate from 8.6% to 10.3% of all crashes year-over-year, indicating an upward trend.
Vulnerable Road User Casualties
0
Motorists Killed
19
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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. In September 2023, the peak day for crashes was Tuesday with 23 incidents, while in September 2024, Monday became the peak day with 18 crashes. The peak crash hour also changed, moving from 5 PM with 11 crashes in the prior period to 4 PM with 14 crashes in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crash rates remained at 0% for both September 2023 and September 2024. The distribution of injury severities saw a change, with 2 crashes resulting in serious injuries (2.3% of total crashes) reported in the current period, a category not present in the prior period's data. Minor injury crashes increased from 6 (7.4% share) to 11 (12.6% share), while possible injury crashes decreased from 5 (6.2% share) to 2 (2.3% share) year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Most severe injury per crash record
Top Contributing Factors
Comparing contributing factors, 'No improper driving' increased by 2 crashes, from 23 to 25, maintaining its top rank. 'Inattention' decreased by 2 crashes, from 18 to 16, while 'Failed to yield right of way' also decreased by 2 crashes, from 9 to 7. Notably, 'Driving too fast for conditions' increased from 0 crashes in the prior period to 2 crashes in the current period, and 'Exceeded authorized speed limit' appeared with 1 crash in the current period where it was absent before.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Road conditions showed a shift towards drier conditions for crashes, with crashes on dry surfaces increasing from 64 to 83, and crashes on wet surfaces decreasing significantly from 17 to 4. Crashes occurring in clear weather conditions increased from 63 to 74, while those in rainy conditions decreased from 11 to 3. Daylight crashes increased from 57 to 66, and crashes at dusk decreased from 5 to 2, while crashes at dawn increased from 0 to 3.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Road surface condition field
Vehicles & Demographics
Toyota remained the most common vehicle make involved in crashes, increasing from 24 to 30 incidents. Honda and Ford, ranked second and third respectively, saw slight decreases in involvement, from 22 to 20 for Honda and 21 to 20 for Ford. The age distribution of persons involved in crashes showed a notable increase of 13 persons in the 21-25 age group (from 18 to 31) and a decrease of 8 persons in the 65+ age group (from 22 to 14).
Top Vehicle Makes (167 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Vehicle unit records
21 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (176 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph speed zones increased from 13 to 18, and in 30 mph zones, they rose from 24 to 30 year-over-year. Conversely, crashes in 35 mph zones decreased from 13 to 10, and in 65 mph zones, they decreased from 8 to 7. There were no fatal crashes reported in any speed limit zone for either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-09-01 to 2024-09-30 · 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: 2024-09-01 through 2024-09-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-09-01 through 2024-09-30 (30 days)
- Geographic scope: MARLBOROUGH, MA
- Total crash records analyzed: 87
- Total persons involved: 202
- Total vehicles involved: 167
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: September 2024." Published June 21, 2026. Reporting period: 2024-09-01 to 2024-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/marlborough/september-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: 2024-09-01 – 2024-09-30
Generated: June 21, 2026 · All rights reserved