ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SALISBURY, MA · AUGUST 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/salisbury/august-2025-report
Monthly Traffic Safety Analysis
30 CRASHES IN
SALISBURY, MA
AUGUST 2025
In August 2025, Salisbury experienced 30 total crashes, a decrease of 9.1% from the 33 crashes reported in August 2024. Despite the reduction in total crashes, the number of total injuries doubled from 5 in the prior year to 10 in the current period. This indicates a shift towards more severe outcomes in the crashes that did occur.
30
▼ -9.1%was 33
Total Crash Events
0
Persons Killed
10
▲ 100.0%was 5
Persons Injured
1
▼ -80.0%was 5
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 · 2025-08-01 to 2025-08-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend shows a slight decrease in total crashes, with 30 crashes in August 2025 compared to 33 in August 2024, representing a 9.1% reduction. However, the number of individuals injured in these crashes saw a significant increase, rising by 100% from 5 to 10 year-over-year.
1
Hit-and-Run Crashes — August 2025
▼ -80.0% vs prior (5)
Hit-and-run crashes significantly decreased from 5 in August 2024 to 1 in August 2025, representing an 80% reduction. The hit-and-run rate also saw a substantial decline, dropping from 15.2% in the prior period to 3.3% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
8
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · 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 only Saturday in August 2024 to both Friday and Saturday in August 2025, with 7 crashes on each day. The peak hour for crashes moved from 4 PM with 5 crashes in the prior period to 3 PM with 4 crashes in the current period. Notably, crashes on Wednesday increased from 0 to 4, while crashes on Tuesday decreased from 7 to 2.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes or fatalities in either August 2025 or August 2024. However, injury severity distributions changed, with serious injuries (A) increasing from 0 to 2, minor injuries (B) increasing from 2 to 3, and possible injuries (C) increasing from 2 to 3. Consequently, crashes resulting in no injury decreased from 28 to 22 year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" saw a substantial increase from 1 to 5, a 400% change in count. Conversely, "No improper driving" as a factor decreased by 6 crashes, from 11 to 5, a 54.5% change in count. "Inattention" also saw a decrease of 4 crashes, from 7 to 3, a 57.1% change in count.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased slightly from 22 in August 2024 to 24 in August 2025. Crashes in daylight decreased from 26 to 19, while crashes in dark conditions on a lighted roadway increased from 3 to 9. The number of crashes on wet road surfaces decreased from 3 to 2 year-over-year.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 65 in August 2024 to 52 in August 2025, a 20% reduction. In terms of top makes, TOYOTA, which was the most frequent make in the prior period with 13 vehicles, decreased to 4, while GMC emerged as the most frequent in the current period with 8 vehicles. The age group 55-64 saw a decrease of 5 persons involved, from 19 to 14, and the 21-25 age group decreased by 4 persons, from 8 to 4.
Top Vehicle Makes (52 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Vehicle unit records
3 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (72 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 40 mph speed zones increased from 7 to 9, while crashes in 5 mph speed zones decreased from 4 to 2. Crashes in 20 mph zones, present in the prior period with 3 occurrences, were absent in the current period. No fatalities were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · 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: 2025-08-01 through 2025-08-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-08-01 through 2025-08-31 (31 days)
- Geographic scope: SALISBURY, MA
- Total crash records analyzed: 30
- Total persons involved: 76
- Total vehicles involved: 52
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). "SALISBURY, MA Crash Intelligence Report: August 2025." Published June 21, 2026. Reporting period: 2025-08-01 to 2025-08-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/salisbury/august-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: 2025-08-01 – 2025-08-31
Generated: June 21, 2026 · All rights reserved