ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · HOPKINTON, MA · SEPTEMBER 2025
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/hopkinton/september-2025-report
Monthly Traffic Safety Analysis
37 CRASHES IN
HOPKINTON, MA
SEPTEMBER 2025
Total crashes in HOPKINTON, MA increased by 23.3% from 30 in September 2024 to 37 in September 2025. Concurrently, the total number of injuries rose significantly from 11 to 19, marking a 72.7% increase year-over-year. The most notable shift was the increase in serious injuries, from 0 to 3, and the emergence of 2 DUI-related crashes in the current period.
37
▲ 23.3%was 30
Total Crash Events
0
Persons Killed
19
▲ 72.7%was 11
Persons Injured
2
▼ -33.3%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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash activity in HOPKINTON, MA shows an upward trend year-over-year. Total crashes increased from 30 in September 2024 to 37 in September 2025, representing a 23.3% rise. This increase was accompanied by a substantial 72.7% surge in total injuries, from 11 to 19.
2
Hit-and-Run Crashes — September 2025
▼ -33.3% vs prior (3)
Hit-and-run crashes decreased from 3 in September 2024 to 2 in September 2025. This resulted in the hit-and-run crash rate falling from 10% to 5.4% year-over-year. The trend indicates a decrease in the proportion of crashes involving a hit-and-run incident.
Vulnerable Road User Casualties
0
Motorists Killed
19
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The distribution of crashes across the week shifted, with Monday and Thursday becoming the days with the highest crash counts in September 2025, each recording 8 crashes, up from 5 and 3 respectively in September 2024. The peak crash hour also moved from 8 AM (6 crashes) in September 2024 to 3 PM and 5 PM (5 crashes each) in September 2025. This indicates a shift in peak crash times from morning to afternoon/evening hours.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatalities reported in either September 2024 or September 2025. However, serious injuries (Severity A) increased from 0 in September 2024 to 3 in September 2025. The total number of injured persons rose from 11 to 19, and the proportion of crashes resulting in any injury increased from 36.7% to 51.4% year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Most severe injury per crash record
Top Contributing Factors
"Followed too closely" remained the leading contributing factor, increasing from 6 crashes in September 2024 to 9 crashes in September 2025, a 50% increase in count. "Failed to yield right of way" also saw a 100% increase, rising from 3 to 6 crashes. Conversely, "Inattention" decreased by 33.3% in count, from 6 crashes to 4 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in daylight conditions increased from 23 in September 2024 to 33 in September 2025. Similarly, crashes on dry road surfaces increased from 26 to 33 year-over-year, while crashes on wet surfaces remained stable at 4. Clear weather conditions continued to be the most common, accounting for the majority of crashes in both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 61 in September 2024 to 77 in September 2025, a 26.2% rise. Toyota's involvement decreased from 16 vehicles to 8, while Ford and Subaru vehicles each increased from 3 to 9. The 21-25 age group saw a notable increase in persons involved, rising from 2 to 7, and the 35-44 age group also increased from 14 to 20.
Top Vehicle Makes (77 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Vehicle unit records
5 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (87 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph zones increased significantly from 2 in September 2024 to 6 in September 2025. Conversely, crashes in 65 mph zones decreased from 11 to 8 during the same period. Additionally, 6 crashes occurred in 40 mph zones in September 2025, a speed limit not represented in the prior year's data.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · 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: 2025-09-01 through 2025-09-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-09-01 through 2025-09-30 (30 days)
- Geographic scope: HOPKINTON, MA
- Total crash records analyzed: 37
- Total persons involved: 93
- Total vehicles involved: 77
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). "HOPKINTON, MA Crash Intelligence Report: September 2025." Published June 21, 2026. Reporting period: 2025-09-01 to 2025-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hopkinton/september-2025-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: 2025-09-01 – 2025-09-30
Generated: June 21, 2026 · All rights reserved