ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MARLBOROUGH, MA · JUNE 2023
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-2023-report
Monthly Traffic Safety Analysis
108 CRASHES IN
MARLBOROUGH, MA
JUNE 2023
In June 2023, Marlborough experienced 108 total crashes, an increase from 96 crashes in June 2022, representing a 12.5% rise year-over-year. The most notable shift was a significant increase in hit-and-run crashes, which quadrupled from 3 to 12 incidents.
108
▲ 12.5%was 96
Total Crash Events
0
Persons Killed
27
▼ -10.0%was 30
Persons Injured
12
▲ 300.0%was 3
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 · 2023-06-01 to 2023-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates an increase in crashes in June 2023 compared to June 2022. Total crashes rose from 96 to 108, marking a 12.5% increase year-over-year. This suggests a rising trend in crash incidents for this period.
12
Hit-and-Run Crashes — June 2023
▲ 300.0% vs prior (3)
Hit-and-run crashes increased significantly year-over-year, rising from 3 incidents in June 2022 to 12 incidents in June 2023. This represents a 300% increase in count. Consequently, the hit-and-run rate also climbed from 3.1% of all crashes in June 2022 to 11.1% in June 2023, indicating an upward trend.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
26
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns for crashes shifted year-over-year. In June 2023, the peak day for crashes was Friday with 25 incidents, whereas in June 2022, Sunday was the peak with 19 crashes. The peak hour also changed, with 2 PM recording the highest number of crashes (17) in June 2023, compared to 3 PM (10 crashes) in June 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero in both June 2023 and June 2022. The proportion of crashes resulting in serious injuries remained consistent at 1 crash in both periods, representing 0.9% of total crashes in June 2023 and 1% in June 2022. However, minor injury crashes decreased from 14 (14.6% share) in June 2022 to 11 (10.2% share) in June 2023, and possible injury crashes decreased from 8 (8.3% share) to 4 (3.7% share).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Most severe injury per crash record
Top Contributing Factors
Several contributing factors saw significant year-over-year changes in crash counts. Crashes attributed to 'Followed too closely' more than doubled, increasing from 8 incidents in June 2022 to 19 in June 2023. 'No improper driving' also increased from 20 to 29 incidents, and 'Inattention' rose from 14 to 18 incidents. Conversely, crashes due to 'Failed to yield right of way' decreased from 16 to 11 incidents, and 'Distracted' crashes decreased from 4 to 2 incidents.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
There were notable shifts in crash conditions year-over-year. Crashes occurring in wet road surface conditions more than doubled, increasing from 6 in June 2022 to 19 in June 2023. Similarly, crashes during rain increased from 3 to 11 incidents, and those at dusk increased from 1 to 6 incidents. Crashes under clear weather conditions decreased slightly from 83 to 80, and on dry road surfaces from 90 to 87.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 184 in June 2022 to 209 in June 2023, a 13.6% rise. While Toyota remained a top make, its involvement decreased from 40 to 36 vehicles. Honda's involvement increased significantly from 20 to 31 vehicles, and Chevrolet's from 10 to 20 vehicles, indicating shifts in the makes most frequently involved in crashes.
Top Vehicle Makes (209 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Vehicle unit records
23 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (261 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 35 mph zones increased from 15 in June 2022 to 23 in June 2023, and crashes in 65 mph zones rose from 14 to 19. Conversely, crashes in 25 mph zones decreased from 19 to 13. No fatal crashes were recorded in any speed zone in either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · 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: 2023-06-01 through 2023-06-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-06-01 through 2023-06-30 (30 days)
- Geographic scope: MARLBOROUGH, MA
- Total crash records analyzed: 108
- Total persons involved: 288
- Total vehicles involved: 209
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 2023." Published June 21, 2026. Reporting period: 2023-06-01 to 2023-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/marlborough/june-2023-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: 2023-06-01 – 2023-06-30
Generated: June 21, 2026 · All rights reserved