ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · ROCHESTER, MA · APRIL 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/rochester/april-2025-report
Monthly Traffic Safety Analysis
6 CRASHES IN
ROCHESTER, MA
APRIL 2025
In April 2025, the city of ROCHESTER experienced 6 total crashes, which is consistent with the 6 crashes reported in April 2024. Despite the stable number of total crashes, there was a significant increase in total injuries, rising from 1 in the prior period to 4 in the current period, representing a 300% increase. The most notable shift was the appearance of serious injury crashes in the current period, with 1 serious injury crash reported compared to none in the prior year.
6
Total Crash Events
0
Persons Killed
4
▲ 300.0%was 1
Persons Injured
0
Fatal Crash Events
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 · 2025-04-01 to 2025-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend for total crashes in ROCHESTER remained stable year-over-year, with 6 crashes recorded in both April 2025 and April 2024. This represents a 0% change in the total number of crash events between the two periods. However, the number of individuals injured in crashes increased from 1 in April 2024 to 4 in April 2025.
Vulnerable Road User Casualties
0
Motorists Killed
4
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · 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 between the two periods. The peak day for crashes changed from Thursday in April 2024, with 2 crashes, to Friday in April 2025, also with 2 crashes. Additionally, the peak hour for crashes shifted from 6 AM with 3 crashes in April 2024 to 12 AM with 2 crashes in April 2025.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While there were no fatal crashes or fatalities in either April 2024 or April 2025, the severity distribution of injury crashes changed notably. Total injuries increased from 1 in April 2024 to 4 in April 2025. In the current period, 1 crash resulted in a serious injury and 2 crashes resulted in minor injuries, whereas the prior period reported only 1 minor injury crash and no serious injury crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Most severe injury per crash record
Top Contributing Factors
The distribution of contributing factors showed shifts year-over-year. Crashes attributed to 'No improper driving' decreased from 3 in April 2024 to 1 in April 2025. Factors such as 'Disregarded traffic signs, signals, road markings,' 'Failed to yield right of way,' 'Operating defective equipment,' and 'Swerving or avoiding' each appeared as a contributing factor in 1 crash in April 2025, none of which were present in April 2024. Conversely, 'Distracted' and 'Inattention' each contributed to 1 crash in April 2024 but were not listed in April 2025.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Regarding crash conditions, crashes occurring in 'Clear' weather decreased from 4 in April 2024 to 2 in April 2025. Crashes in 'Dark - roadway not lighted' conditions increased from 2 in the prior period to 3 in the current period, while 'Daylight' crashes remained stable at 3 in both periods. For road surface conditions, 'Dry' surface crashes increased from 4 to 5, and 'Wet' surface crashes decreased from 2 to 1.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Road surface condition field
Vehicles & Demographics
Top Vehicle Makes (9 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Vehicle unit records
Sex Distribution (9 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones saw some changes, though no fatal crashes occurred in any zone in either period. Crashes in the 45 mph speed zone increased from 1 in April 2024 to 2 in April 2025. While the 20 mph and 40 mph zones remained stable with 1 and 2 crashes respectively, crashes in the 30 mph and 35 mph zones (1 crash each in April 2024) were not present in April 2025, and a crash in the 65 mph zone appeared in April 2025 (1 crash) but not in April 2024.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-04-01 to 2025-04-30 · 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: 2025-04-01 through 2025-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-04-01 through 2025-04-30 (30 days)
- Geographic scope: ROCHESTER, MA
- Total crash records analyzed: 6
- Total persons involved: 10
- Total vehicles involved: 9
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). "ROCHESTER, MA Crash Intelligence Report: April 2025." Published June 21, 2026. Reporting period: 2025-04-01 to 2025-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/rochester/april-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: 2025-04-01 – 2025-04-30
Generated: June 21, 2026 · All rights reserved