ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · HUBBARDSTON, MA · 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/hubbardston/2025-annual-report
Yearly Traffic Safety Analysis
60 CRASHES IN
HUBBARDSTON, MA
2025
In 2025, Hubbardston recorded 60 total traffic crashes, a 7.1% increase from the 56 crashes reported in 2024. While total injuries decreased slightly from 14 to 13 and fatalities remained at zero, the data shows a notable increase in single-vehicle crashes, which rose from 37 to 51 year-over-year. Another significant shift was the rise in collisions occurring on icy road surfaces, which more than doubled from 6 to 15 incidents.
60
▲ 7.1%was 56
Total Crash Events
0
Persons Killed
13
▼ -7.1%was 14
Persons Injured
1
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 · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, traffic collisions in Hubbardston trended upward, with a 7.1% increase from 56 crashes in 2024 to 60 in 2025. Despite the rise in total incidents, the number of resulting injuries saw a slight decrease from 14 to 13. There were no fatal crashes recorded in either period.
1
Hit-and-Run Crashes — 2025
▼ 0.0% vs prior (1)
The number of hit-and-run incidents remained stable, with one crash reported in both 2024 and 2025. Due to the overall increase in total collisions in the current year, the hit-and-run rate saw a marginal decrease from 1.8% of all crashes in 2024 to 1.7% in 2025.
Vulnerable Road User Casualties
0
Motorists Killed
13
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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 year-over-year. In 2025, the peak day for crashes was Thursday with 11 incidents, a change from the prior year's peak on Tuesday, which saw 14 crashes. Similarly, the peak hour for collisions moved from the afternoon commute hours of 3 p.m. and 5 p.m. in 2024 (6 crashes each) to the late evening at 10 p.m. in 2025 (7 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity remained relatively stable between the two periods, with no fatalities recorded in either 2024 or 2025. The total number of crashes involving an injury was unchanged at 11 incidents for both years. However, as a proportion of all collisions, injury-related crashes decreased from a 19.6% share in 2024 to an 18.3% share in 2025, while the share of no-injury crashes rose from 76.8% to 81.7%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
In both years, 'No improper driving' was the most cited factor, with its count increasing by 30.8% from 26 incidents in 2024 to 34 in 2025. The count of crashes attributed to an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' increased from 1 to 4. Conversely, crashes involving 'Failed to yield right of way' decreased from a count of 4 in the prior year to just 1 in the current year.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
A significant shift occurred in the road surface conditions associated with crashes, as collisions on icy roads increased from 6 incidents in 2024 to 15 in 2025. Correspondingly, crashes on dry surfaces decreased from 32 to 25. Collisions in dark conditions also increased, rising from 20 incidents in the prior year to 26 in the current year, with most of these occurring on unlighted roadways in both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
Ford remained the most common vehicle make involved in crashes, with its count rising from 15 in 2024 to 18 in 2025, while Toyota's involvement decreased from 14 vehicles to 7. Regarding persons involved, the 26-34 age group was the largest cohort in both years, though its count fell from 20 to 16. A notable shift occurred in the 16-20 age group, where the number of individuals involved in crashes increased from 7 to 13.
Top Vehicle Makes (72 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
4 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (89 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
In both 2024 and 2025, the highest number of crashes occurred in 40 mph speed zones, with the count in this zone increasing from 24 to 31 incidents year-over-year. Conversely, collisions in 45 mph zones decreased from 14 to 10. Crashes in 30 mph zones remained stable with 8 incidents in both periods. No fatal crashes were recorded in any speed zone for either year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: HUBBARDSTON, MA
- Total crash records analyzed: 60
- Total persons involved: 93
- Total vehicles involved: 72
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). "HUBBARDSTON, MA Crash Intelligence Report: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/hubbardston/2025-annual-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved