ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SEEKONK, MA · DECEMBER 2024
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/december-2024-report
Monthly Traffic Safety Analysis
85 CRASHES IN
SEEKONK, MA
DECEMBER 2024
In December 2024, SEEKONK experienced 85 crashes, a slight decrease of 1.16% compared to the 86 crashes recorded in December 2023. Total injuries decreased by 15.38% from 26 to 22. The most notable shift was a 100% increase in speeding-related crashes, rising from 2 to 4.
85
▼ -1.2%was 86
Total Crash Events
0
Persons Killed
22
▼ -15.4%was 26
Persons Injured
6
▲ 20.0%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. 9 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the total number of crashes in SEEKONK remained relatively stable year-over-year, with a minor decrease of 1.16% from 86 crashes in December 2023 to 85 crashes in December 2024. While total fatalities remained at zero, total injuries saw a more significant reduction of 15.38%, decreasing from 26 to 22.
6
Hit-and-Run Crashes — December 2024
▲ 20.0% vs prior (5)
Hit-and-run crashes increased from 5 in December 2023 to 6 in December 2024. The hit-and-run crash rate also increased from 5.8% in the prior period to 7.1% in the current period, indicating an upward trend.
Vulnerable Road User Casualties
0
Motorists Killed
22
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · 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 Thursday in December 2023, with 16 crashes, to Monday in December 2024, with 19 crashes. The peak hour also changed from 3 PM (10 crashes) in the prior period to 5 PM (11 crashes) in the current period. Monday crashes increased from 11 in the prior period to 19 in the current period, while Thursday crashes decreased from 16 to 12.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes or fatalities reported in either December 2023 or December 2024. Total injuries decreased from 26 in December 2023 to 22 in December 2024, a reduction of 15.38%. The proportion of crashes resulting in a possible injury increased from 12.8% in the prior period to 16.5% in the current period, while minor injury crashes decreased slightly from 7% to 5.9%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The count of crashes attributed to 'Inattention' decreased by 39.3%, from 28 in December 2023 to 17 in December 2024, though it remained the leading factor. Crashes due to 'Failed to yield right of way' decreased from 17 to 9, and 'Followed too closely' decreased from 10 to 9. The count for 'No improper driving' remained consistent at 14 crashes in both periods.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather decreased from 70 in December 2023 to 52 in December 2024. Conversely, crashes during rainy conditions doubled from 5 to 10, and those on wet road surfaces increased from 13 to 21. There was a notable increase in crashes occurring in 'Dark - lighted roadway' conditions, rising from 8 to 21.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
Toyota and Honda remained the top two vehicle makes involved in crashes, with Toyota decreasing from 26 to 24 and Honda from 23 to 21. Ford saw a significant decrease in involvement, from 22 vehicles in December 2023 to 12 in December 2024. The largest age group involved in crashes shifted from 35-44 year olds (40 persons) in the prior period to 26-34 year olds (34 persons) in the current period.
Top Vehicle Makes (163 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Vehicle unit records
12 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (188 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
The 40 mph speed zone continued to account for the highest number of crashes, increasing from 26 in December 2023 to 37 in December 2024. Crashes in the 30 mph zone increased from 9 to 11, while those in the 35 mph zone decreased from 15 to 6. No fatal crashes were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · 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: 2024-12-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-12-01 through 2024-12-31 (31 days)
- Geographic scope: SEEKONK, MA
- Total crash records analyzed: 85
- Total persons involved: 203
- Total vehicles involved: 163
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: December 2024." Published June 21, 2026. Reporting period: 2024-12-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/seekonk/december-2024-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: 2024-12-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved