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YEAR-OVER-YEAR CRASH REPORT · SEEKONK, MA · APRIL 2023
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/april-2023-report
Monthly Traffic Safety Analysis
56 CRASHES IN
SEEKONK, MA
APRIL 2023
In April 2023, SEEKONK, MA experienced a 16.7% increase in total crashes compared to April 2022, rising from 48 to 56 incidents. Total injuries also increased by 33.3%, from 6 to 8, while fatalities remained at zero in both periods. The most notable year-over-year shift was a 400% increase in hit-and-run crashes, which rose from 1 to 5.
56
▲ 16.7%was 48
Total Crash Events
0
Persons Killed
8
▲ 33.3%was 6
Persons Injured
5
▲ 400.0%was 1
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. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash activity in SEEKONK, MA showed an upward trend year-over-year. Total crashes increased by 8 incidents, representing a 16.7% rise from 48 crashes in April 2022 to 56 crashes in April 2023. Similarly, total injuries rose by 2, a 33.3% increase from 6 to 8, while fatal crashes remained at zero in both periods.
5
Hit-and-Run Crashes — April 2023
▲ 400.0% vs prior (1)
Hit-and-run crashes increased substantially year-over-year, rising from 1 incident in April 2022 to 5 incidents in April 2023, representing a 400% increase in count. This led to a significant increase in the hit-and-run rate, which climbed from 2.1% to 8.9% of all crashes.
Vulnerable Road User Casualties
0
Motorists Killed
8
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · 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 Saturday with 11 incidents in April 2022 to Thursday with 11 incidents in April 2023. The peak hour also changed, moving from 2 PM with 6 crashes in April 2022 to 1 PM with 15 crashes in April 2023, indicating a significant concentration of crashes around midday in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either April 2022 or April 2023. The number of minor injuries increased by 100%, rising from 2 in the prior period to 4 in the current period. While serious injuries were reported in the prior period (1 crash), none were recorded in the current period, and possible injuries remained stable at 2 crashes in both periods.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Most severe injury per crash record
Top Contributing Factors
The count of crashes attributed to 'Inattention' decreased slightly from 21 in April 2022 to 20 in April 2023, with its share of factors decreasing from 43.8% to 35.7%. Conversely, 'No improper driving' crashes increased from 5 to 12, a 140% rise, causing its share to grow from 10.4% to 21.4% and moving it from third to second most common factor. Crashes due to 'Failed to yield right of way' decreased by 4, from 10 to 6, while 'Followed too closely' crashes increased by 2, from 3 to 5.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased from 41 in April 2022 to 43 in April 2023. Incidents during 'Cloudy' weather saw a 250% increase, rising from 2 to 7, and 'Wet' road surface conditions increased by 5 crashes, from 4 to 9. The number of crashes in 'Daylight' conditions increased by 10, from 39 to 49, while those in 'Dark - lighted roadway' decreased by 2, from 6 to 4.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 87 in April 2022 to 105 in April 2023. Toyota remained the top make, with its involvement increasing from 17 to 18 vehicles, while Chevrolet saw a 140% increase, rising from 5 to 12 vehicles and moving from fourth to second in rankings. Conversely, Ford involvement decreased from 11 to 8, shifting its rank from second to third. The 0-15 age group saw a substantial increase in persons involved, from 2 to 11, while the 16-20 age group decreased from 19 to 7.
Top Vehicle Makes (105 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Vehicle unit records
8 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (117 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 40 mph speed zone increased by 6, from 16 in April 2022 to 22 in April 2023, making it the most frequent speed zone for crashes in both periods. Crashes in the 65 mph zone increased significantly from 1 to 6. Conversely, crashes in the 25 mph zone decreased by 4, from 7 to 3. No fatalities were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · 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: 2023-04-01 through 2023-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-04-01 through 2023-04-30 (30 days)
- Geographic scope: SEEKONK, MA
- Total crash records analyzed: 56
- Total persons involved: 126
- Total vehicles involved: 105
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: April 2023." Published June 21, 2026. Reporting period: 2023-04-01 to 2023-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/seekonk/april-2023-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: 2023-04-01 – 2023-04-30
Generated: June 21, 2026 · All rights reserved