ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MARLBOROUGH, MA · JULY 2022
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/july-2022-report
Monthly Traffic Safety Analysis
67 CRASHES IN
MARLBOROUGH, MA
JULY 2022
Total crashes in MARLBOROUGH, MA decreased by 16.25% from 80 crashes in July 2021 to 67 crashes in July 2022. This represents a reduction of 13 crashes year-over-year. A notable shift was the 50% increase in hit-and-run crashes, rising from 2 in July 2021 to 3 in July 2022.
67
▼ -16.3%was 80
Total Crash Events
0
Persons Killed
22
▼ -8.3%was 24
Persons Injured
3
▲ 50.0%was 2
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. 4 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend for crashes in MARLBOROUGH, MA is downward, with total crashes decreasing by 16.25% from 80 in July 2021 to 67 in July 2022. Total injuries also saw a decrease of 8.33%, from 24 in July 2021 to 22 in July 2022.
3
Hit-and-Run Crashes — July 2022
▲ 50.0% vs prior (2)
Hit-and-run crashes increased by 1, from 2 in July 2021 to 3 in July 2022. This resulted in an increase in the hit-and-run rate from 2.5% of all crashes in July 2021 to 4.5% in July 2022, indicating an upward trend in the proportion of hit-and-run incidents.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
21
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Thursday in July 2021 (16 crashes) to Friday in July 2022 (15 crashes), though Friday's count remained stable year-over-year. The peak hour for crashes also shifted from 3 PM in July 2021 (8 crashes) to 5 PM in July 2022 (9 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either period. The number of crashes resulting in minor injuries decreased from 15 (18.8% share) in July 2021 to 9 (13.4% share) in July 2022. Conversely, crashes with possible injuries increased from 1 (1.3% share) in July 2021 to 5 (7.5% share) in July 2022.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Most severe injury per crash record
Top Contributing Factors
The count of crashes attributed to 'Followed too closely' decreased by 5, from 13 in July 2021 to 8 in July 2022, representing a 38.5% reduction. Crashes where 'Failed to yield right of way' was a factor decreased by 4, from 10 to 6, a 40% reduction. Meanwhile, crashes with 'No improper driving' as a factor increased by 2, from 15 to 17, a 13.3% increase.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring on wet road surfaces decreased significantly from 17 in July 2021 to 2 in July 2022, while crashes on dry surfaces remained relatively stable (62 in July 2021 vs. 65 in July 2022). Crashes under clear weather conditions increased from 53 in July 2021 to 59 in July 2022, even as total crashes decreased. The number of crashes occurring in daylight decreased from 64 to 54, while those in dark conditions remained constant at 12.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased by 20.1%, from 159 in July 2021 to 127 in July 2022. While Toyota remained the top make involved, its count decreased from 32 to 23. Honda's involvement decreased from 25 to 11, while Nissan's involvement increased from 7 to 16, moving it into the top three makes.
Top Vehicle Makes (127 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Vehicle unit records
13 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (127 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 30 mph zones saw the largest decrease, dropping by 10 from 28 in July 2021 to 18 in July 2022. Crashes in 65 mph zones also decreased by 5, from 15 to 10. Conversely, crashes in 25 mph zones increased by 3, from 7 to 10.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · 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: 2022-07-01 through 2022-07-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-07-01 through 2022-07-31 (31 days)
- Geographic scope: MARLBOROUGH, MA
- Total crash records analyzed: 67
- Total persons involved: 149
- Total vehicles involved: 127
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: July 2022." Published June 21, 2026. Reporting period: 2022-07-01 to 2022-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/marlborough/july-2022-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: 2022-07-01 – 2022-07-31
Generated: June 21, 2026 · All rights reserved