Monthly Traffic Safety Analysis

68 CRASHES IN
SEEKONK, MA
JULY 2023

All metrics benchmarked againstJuly 2022

In July 2023, SEEKONK experienced 68 crashes, an 11.48% increase compared to the 61 crashes recorded in July 2022. Total injuries rose by 36.36%, from 11 to 15, while fatalities remained at zero in both periods. A notable shift was the emergence of 5 hit-and-run crashes in July 2023, compared to none in July 2022.

68

11.5%was 61

Total Crash Events

0

Persons Killed

15

36.4%was 11

Persons Injured

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. 21 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for SEEKONK shows an upward trend year-over-year, with total crashes increasing from 61 in July 2022 to 68 in July 2023. This represents an 11.48% rise in the number of incidents. Concurrently, total injuries also increased significantly by 36.36%, from 11 to 15 persons injured.

5

Hit-and-Run Crashes — July 2023

7.4% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

14

Motorists Injured

Prior: 1040.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · 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 Friday with 12 incidents in July 2022 to Thursday with 17 incidents in July 2023. Similarly, the peak hour for crashes moved from 6 PM with 8 incidents in the prior period to 2 PM with 11 incidents in the current period. Crashes on Wednesday also saw a substantial increase, rising from 6 to 13 year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero in both July 2022 and July 2023, indicating no change in the fatal crash rate. However, the proportion of minor injury crashes (severity B) increased from 6.6% (4 crashes) in the prior period to 13.2% (9 crashes) in the current period. Conversely, crashes resulting in possible injuries (severity C) decreased from 8.2% (5 crashes) to 4.4% (3 crashes), and crashes with no injuries (severity O) decreased from 65.6% (40 crashes) to 51.5% (35 crashes).

Outcome by Severity (Crash Events)

Minor Injury9minor injury crashes13.2%
125.0%prior 4
Possible Injury3possible injury crashes4.4%
-40.0%prior 5
No Injury35no injury crashes51.5%
-12.5%prior 40

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'Inattention' increased by 5 crashes, from 21 in July 2022 to 26 in July 2023, maintaining its position as the top factor. Crashes attributed to 'Followed too closely' decreased by 5, from 9 to 4, causing its rank to drop from third to fourth. 'Failed to yield right of way' saw a slight increase of 1 crash, from 7 to 8, and rose in rank from fourth to third.

Officer-Reported Primary Contributing Cause

Inattention26 (38.2%)23.8%prior 21
No improper driving14 (20.6%)27.3%prior 11
Failed to yield right of way8 (11.8%)14.3%prior 7
Followed too closely4 (5.9%)-55.6%prior 9
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (2.9%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (2.9%)
Exceeded authorized speed limit1 (1.5%)
Driving too fast for conditions1 (1.5%)
Other improper action1 (1.5%)
Over-correcting/over-steering1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions increased from 53 in July 2022 to 63 in July 2023, while those in 'Cloudy' conditions decreased from 7 to 3. Crashes during 'Daylight' increased from 55 to 57, and incidents during 'Dusk' increased from 1 to 2. The number of crashes on 'Dry' road surfaces rose from 58 to 65, while crashes on 'Wet' road surfaces remained stable at 3 in both periods.

Weather

Clear63 (92.6%)
18.9%prior 53
Cloudy3 (4.4%)
-57.1%prior 7
Rain2 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Weather condition at time of crash

Lighting

Daylight57 (85.1%)
3.6%prior 55
Dark - roadway not lighted3 (4.5%)
Dark - lighted roadway3 (4.5%)
Dusk2 (3.0%)
Dawn1 (1.5%)
Dark - unknown roadway lighting1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Lighting condition field

Road Surface

Dry65 (95.6%)
12.1%prior 58
Wet3 (4.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Road surface condition field

Vehicles & Demographics

The age distribution of persons involved in crashes showed notable shifts, with the 35-44 age group increasing from 20 to 33 persons and the 45-54 age group increasing from 8 to 23 persons. Conversely, the 0-15 age group decreased from 14 to 6 persons, and the 65+ age group decreased from 23 to 18 persons. Regarding top vehicle makes, TOYOTA saw a significant increase in involvement from 11 to 22 vehicles, becoming the most frequently involved make, while FORD's involvement decreased from 20 to 7 vehicles.

Top Vehicle Makes (129 vehicles)

1
TOYOTA22 (17.1%)
100.0%prior 11
2
HONDA13 (10.1%)
18.2%prior 11
3
NISSAN10 (7.8%)
42.9%prior 7
4
CHEVROLET8 (6.2%)
-11.1%prior 9
5
SUBARU8 (6.2%)
6
FORD7 (5.4%)
-65.0%prior 20
7
KIA7 (5.4%)
8
HYUNDAI6 (4.7%)
20.0%prior 5
9
VOLKSWAGEN5 (3.9%)
10
MAZDA5 (3.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Vehicle unit records

10 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (142 persons with recorded sex)

Male73 (51.4%)
-11.0%prior 82
Female69 (48.6%)
9.5%prior 63

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · Person-level records linked to crash events

Speed Limit Zones

There were no fatal crashes in any speed zone during either period. Crashes in 35 mph speed zones saw a substantial increase, rising from 9 in July 2022 to 21 in July 2023. Conversely, crashes in 40 mph speed zones decreased from 18 to 15, and those in 65 mph zones decreased from 6 to 3. Crashes in 50 mph speed zones doubled from 2 to 4 year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-07-01 to 2023-07-31 · 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: 2023-07-01 through 2023-07-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-07-01 through 2023-07-31 (31 days)
  • Geographic scope: SEEKONK, MA
  • Total crash records analyzed: 68
  • Total persons involved: 167
  • Total vehicles involved: 129

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: July 2023." Published June 21, 2026. Reporting period: 2023-07-01 to 2023-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/seekonk/july-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

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Seekonk, MA Crash Report — July 2023 | ThatCarHitMe.com