ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · BLANDFORD, 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/blandford/2025-annual-report
Yearly Traffic Safety Analysis
59 CRASHES IN
BLANDFORD, MA
2025
In Blandford, total vehicle crashes decreased by 28.9% from 83 incidents in 2024 to 59 in 2025. This overall reduction in crashes was accompanied by a drop in total injuries from 26 to 17. The most significant year-over-year change was the elimination of traffic fatalities, which fell from one death in the prior period to zero in the current period.
59
▼ -28.9%was 83
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
17
▼ -34.6%was 26
Persons Injured
4
▲ 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 · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic safety trends in Blandford show a notable improvement year-over-year. The total number of crashes fell from 83 to 59, a 28.9% decrease. Similarly, the number of people injured in these incidents declined by 34.6%, from 26 to 17, and fatalities were reduced from one to zero.
4
Hit-and-Run Crashes — 2025
▲ 33.3% vs prior (3)
While overall crashes decreased, hit-and-run incidents trended upward. The absolute number of hit-and-run crashes increased from 3 in 2024 to 4 in 2025. As a result of the lower total crash volume, the hit-and-run rate nearly doubled, rising from 3.6% of all crashes in the prior year to 6.8% in the current year.
Vulnerable Road User Casualties
0
Motorists Killed
17
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 showed some consistency and some shifts between the two periods. Sunday remained a peak day for crashes in both years, though the count dropped from 17 in 2024 (tied with Monday) to 12 in 2025. The peak hour for collisions shifted slightly earlier, from 9 p.m. in the prior year (9 crashes) to 8 p.m. in the current year (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 decreased significantly year-over-year. The prior period recorded one fatal crash, accounting for 1.2% of all incidents, while the current period had none. The proportion of crashes resulting in any form of injury (serious, minor, or possible) decreased from a combined 19.2% in 2024 to 15.3% in 2025. Consequently, the share of crashes with no reported injuries increased from 78.3% to 84.7%.
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
The leading contributing factors remained consistent, though their counts changed. In both periods, "No improper driving" was the most cited factor, followed by "Driving too fast for conditions." The number of crashes attributed to driving too fast for conditions saw a substantial decrease, falling from 19 incidents in 2024 to 6 in 2025, a 68.4% reduction in count. Conversely, crashes involving "Inattention" increased from 1 to 5.
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
The conditions under which crashes occurred shifted toward clearer weather and drier roads. The proportion of crashes on non-dry road surfaces (wet, snow, ice, or slush) decreased from 44.6% in 2024 to 33.9% in 2025. Correspondingly, crashes during daylight hours made up a larger share of the total, increasing from 47.0% to 52.5%, while the proportion of crashes in darkness remained relatively stable.
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
The makes of vehicles involved in crashes saw a shift in rankings. In 2024, Toyota was the most involved make with 19 vehicles, but this number dropped to 6 in 2025. Honda became the most involved make in the current period with 10 vehicles, up from 8 in the prior year. Regarding driver demographics, the proportion of persons aged 16-25 involved in crashes decreased from 27.1% of all persons in 2024 to 20.3% in 2025.
Top Vehicle Makes (86 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
9 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (107 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
Crashes became more concentrated in high-speed zones year-over-year. While the absolute number of crashes in 65 mph zones decreased from 59 to 49, their share of all crashes with a recorded speed limit rose from 71.1% to 87.5%. The single fatal crash recorded in 2024 occurred in a 30 mph zone; no fatalities were recorded in any speed zone in 2025.
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: BLANDFORD, MA
- Total crash records analyzed: 59
- Total persons involved: 118
- Total vehicles involved: 86
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). "BLANDFORD, 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/blandford/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