ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SWANSEA, MA · APRIL 2026
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/swansea/april-2026-report
Monthly Traffic Safety Analysis
31 CRASHES IN
SWANSEA, MA
APRIL 2026
In April 2026, Swansea experienced 31 crashes, a decrease of 8.82% compared to the 34 crashes recorded in April 2025. A notable change was the increase in fatalities, with one fatality reported in the current period compared to none in the prior year.
31
▼ -8.8%was 34
Total Crash Events
1
Persons Killed
6
▼ -14.3%was 7
Persons Injured
4
▲ 100.0%was 2
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 · 2026-04-01 to 2026-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, total crashes in Swansea decreased by 8.82% year-over-year, from 34 crashes in April 2025 to 31 crashes in April 2026. However, the number of fatalities increased from 0 to 1 during this period, while total injuries saw a slight decrease from 7 to 6.
4
Hit-and-Run Crashes — April 2026
▲ 100.0% vs prior (2)
Hit-and-run crashes increased year-over-year, rising from 2 crashes in April 2025 to 4 crashes in April 2026. This resulted in the hit-and-run rate more than doubling, from 5.9% of all crashes in the prior period to 12.9% in the current period.
Vulnerable Road User Casualties
1
Motorists Killed
6
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes shifted year-over-year, with the peak day moving from Saturday in April 2025 (8 crashes) to Friday in April 2026 (10 crashes). Similarly, the peak hour for crashes changed from 12 PM (6 crashes) in the prior period to 3 PM (4 crashes) in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The current period recorded one fatal crash, compared to zero in April 2025. Serious injuries decreased from two in the prior period to zero, while minor injuries increased from three to four. The proportion of crashes resulting in any injury remained similar, at 19.35% (6 out of 31 crashes) in April 2026 compared to 20.59% (7 out of 34 crashes) in April 2025.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'No improper driving' saw a significant increase, rising from 3 crashes in April 2025 to 8 crashes in April 2026. 'Inattention' also increased from 4 to 6 crashes, and 'Followed too closely' rose from 2 to 4 crashes. Conversely, 'Failed to yield right of way' decreased notably from 8 crashes in the prior period to 4 crashes in the current period.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The majority of crashes in both periods occurred under clear weather and dry road conditions. Crashes under 'Clear' weather decreased from 18 to 16, while crashes during 'Rain' increased from 1 to 3. The number of crashes occurring in 'Dark - lighted roadway' conditions decreased from 5 in April 2025 to 2 in April 2026.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Road surface condition field
Vehicles & Demographics
The age distribution of persons involved in crashes showed some shifts, with individuals aged 45-54 seeing an increase from 6 to 12 persons, while those aged 26-34 and 65+ both decreased from 13 to 9 persons. Regarding vehicle makes, Ford-involved crashes decreased from 13 to 5 vehicles, while Honda-involved crashes increased from 3 to 5 vehicles.
Top Vehicle Makes (59 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Vehicle unit records
12 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (67 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Person-level records linked to crash events
Speed Limit Zones
A fatal crash occurred in a 40 mph speed zone in April 2026, where no fatal crashes were recorded in any speed zone in April 2025. Crashes in 65 mph zones significantly increased from 2 to 9, making it the zone with the most crashes in the current period. Conversely, crashes in 30 mph zones decreased from 6 to 2, and 50 mph zones decreased from 5 to 1.
Fatal crashes by zone: 40 mph: 1 of 7 (14.286%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · 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: 2026-04-01 through 2026-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2026-04-01 through 2026-04-30 (30 days)
- Geographic scope: SWANSEA, MA
- Total crash records analyzed: 31
- Total persons involved: 78
- Total vehicles involved: 59
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). "SWANSEA, MA Crash Intelligence Report: April 2026." Published June 21, 2026. Reporting period: 2026-04-01 to 2026-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/swansea/april-2026-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: 2026-04-01 – 2026-04-30
Generated: June 21, 2026 · All rights reserved