ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SEEKONK, MA · JUNE 2022
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/seekonk/june-2022-report
Monthly Traffic Safety Analysis
55 CRASHES IN
SEEKONK, MA
JUNE 2022
Total crashes in Seekonk decreased slightly from 57 in June 2021 to 55 in June 2022, representing a 3.5% reduction. However, a significant shift occurred in crash outcomes, with fatalities increasing from 0 to 2 and total injuries decreasing by 75% from 28 to 7 year-over-year. The most notable year-over-year shift was the emergence of fatal crashes, with 1 incident resulting in 2 fatalities in the current period.
55
▼ -3.5%was 57
Total Crash Events
2
Persons Killed
7
▼ -75.0%was 28
Persons Injured
0
▼ -100.0%was 3
Hit-and-Run Crashes
Note: "Persons Killed" (2) 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. 7 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the number of crashes in June 2022 remained relatively stable, with a slight decrease of 3.5% from 57 crashes in June 2021 to 55 crashes. Despite this minor reduction in total incidents, there was a concerning increase in fatalities from 0 to 2, while total injuries saw a substantial 75% decrease from 28 to 7. This indicates a shift towards more severe, albeit fewer, crash outcomes.
Vulnerable Road User Casualties
2
Motorists Killed
0
Other Killed
6
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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 Wednesday and Sunday in June 2021 (both with 11 crashes) to Friday and Thursday in June 2022 (both with 11 crashes). The peak hour also changed, moving from 3 p.m. with 8 crashes in the prior period to 5 p.m. and 12 p.m. with 7 crashes each in the current period. This indicates a shift in high-crash times towards later afternoon and midday.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution of crashes saw a notable increase in fatal outcomes, with 1 fatal crash and 2 fatalities recorded in June 2022 compared to 0 fatal crashes and 0 fatalities in June 2021. Concurrently, crashes resulting in minor injuries decreased from 13 (22.8% of crashes) to 4 (7.3% of crashes), and serious injuries (code A) were reported in 3 crashes (5.3%) in June 2021 but none in June 2022. The proportion of crashes with no reported injury increased from 54.4% to 74.5% year-over-year.
Severity is per crash event (most severe injury). 1 fatal crash events resulted in 2 persons killed.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, "Inattention" saw a substantial increase, rising from 6 crashes in June 2021 to 20 crashes in June 2022, representing a 233.3% increase and becoming the leading factor at 36.4% share. "Failed to yield right of way" also increased significantly from 1 crash to 6 crashes, a 500% rise, and its share grew from 1.8% to 10.9%. Conversely, "Followed too closely" remained constant at 6 crashes in both periods, though its share of crashes slightly increased from 10.5% to 10.9%.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Weather conditions remained largely consistent, with 51 crashes occurring in "Clear" weather in both periods, and a slight reduction in "Wet" road surface crashes from 4 to 2. Lighting conditions showed a shift, with "Daylight" crashes increasing from 45 to 49, while crashes occurring in "Dark - roadway not lighted" decreased from 8 to 0, replaced by 4 crashes in "Dark - lighted roadway" in the current period. Overall, adverse conditions like rain and wet roads saw a slight decrease in crash counts.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Road surface condition field
Vehicles & Demographics
The total number of persons involved in crashes decreased from 140 in June 2021 to 129 in June 2022. Notably, the 16-20 age group saw a significant reduction in involved persons, decreasing from 22 to 7, while the 65+ age group increased from 13 to 19 persons. Among vehicle makes, TOYOTA remained the most frequently involved, though its count decreased from 17 to 15, and NISSAN moved up in ranking with an increase from 8 to 11 vehicles involved.
Top Vehicle Makes (98 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Vehicle unit records
2 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (125 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 40 mph zones increased from 16 in June 2021 to 22 in June 2022, while crashes in 65 mph zones decreased from 7 to 3. The 50 mph speed zone recorded 2 crashes in both periods; however, the current period saw 1 fatal crash in this zone, compared to 0 in the prior period. Crashes in 35 mph zones decreased from 12 to 10, and 30 mph zones decreased from 11 to 8.
Fatal crashes by zone: 50 mph: 1 of 2 (50%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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: 2022-06-01 through 2022-06-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-06-01 through 2022-06-30 (30 days)
- Geographic scope: SEEKONK, MA
- Total crash records analyzed: 55
- Total persons involved: 129
- Total vehicles involved: 98
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). "SEEKONK, MA Crash Intelligence Report: June 2022." Published June 21, 2026. Reporting period: 2022-06-01 to 2022-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/seekonk/june-2022-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: 2022-06-01 – 2022-06-30
Generated: June 21, 2026 · All rights reserved