Monthly Traffic Safety Analysis

14 CRASHES IN
MATTAPOISETT, MA
NOVEMBER 2023

All metrics benchmarked againstNovember 2022

In November 2023, MATTAPOISETT experienced 14 total crashes, marking a 22.2% decrease compared to the 18 crashes recorded in November 2022. This period also saw a 50% reduction in total injuries, falling from 2 to 1. A notable year-over-year shift was the significant decrease in crashes occurring at a 65 mph speed limit, which dropped from 5 to 1 crash.

14

-22.2%was 18

Total Crash Events

0

Persons Killed

1

-50.0%was 2

Persons Injured

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in MATTAPOISETT decreased year-over-year, with total crashes falling from 18 in November 2022 to 14 in November 2023. This represents a 22.2% reduction in crash volume. Concurrently, total injuries decreased by 50%, from 2 to 1.

1

Hit-and-Run Crashes — November 2023

0.0% vs prior (1)

The number of hit-and-run crashes remained constant at 1 in both November 2022 and November 2023. However, the hit-and-run rate increased from 5.6% of total crashes in the prior period to 7.1% in the current period, due to the overall decrease in total crashes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

1

Motorists Injured

Prior: 2-50.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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 between periods. In November 2023, Wednesday and Thursday were the peak crash days with 4 crashes each, while November 2022's peak day was Friday with 4 crashes. The peak crash hour also changed, moving from 11 PM with 3 crashes in the prior period to 5 PM with 3 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero in both November 2022 and November 2023. Minor injury crashes decreased from 2 (11.1% of total crashes) in the prior period to 1 (7.1% of total crashes) in the current period. Crashes resulting in no injury represented 92.9% of all crashes in November 2023, up from 83.3% in November 2022.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes7.1%
-50.0%prior 2
No Injury13no injury crashes92.9%
-13.3%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Most severe injury per crash record

Top Contributing Factors

The count of crashes where 'No improper driving' was cited as a contributing factor decreased from 11 in November 2022 to 6 in November 2023, a 45.5% reduction. Crashes attributed to 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased from 3 to 0. Conversely, crashes involving 'Exceeded authorized speed limit' increased from 0 to 1, and 'Failed to yield right of way' increased from 0 to 1.

Officer-Reported Primary Contributing Cause

No improper driving6 (42.9%)-45.5%prior 11
Exceeded authorized speed limit1 (7.1%)
Failed to yield right of way1 (7.1%)
Failure to keep in proper lane or running off road1 (7.1%)
Followed too closely1 (7.1%)
Inattention1 (7.1%)
Wrong side or wrong way1 (7.1%)
Distracted1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 15 in November 2022 to 11 in November 2023, while 'Cloudy' conditions saw a slight increase from 2 to 3 crashes. For lighting conditions, crashes in 'Dark - roadway not lighted' decreased from 5 to 2, and 'Daylight' crashes decreased from 7 to 6. Data for road surface conditions was not available for the prior period.

Weather

Clear11 (78.6%)
-26.7%prior 15
Cloudy3 (21.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Weather condition at time of crash

Lighting

Dark - lighted roadway6 (42.9%)
0.0%prior 6
Daylight6 (42.9%)
-14.3%prior 7
Dark - roadway not lighted2 (14.3%)
-60.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Lighting condition field

Road Surface

Dry9 (64.3%)
Wet3 (21.4%)
Sand, mud, dirt, oil, gravel2 (14.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (20 vehicles)

1
HONDA4 (20%)
-20.0%prior 5
2
TOYOTA3 (15%)
3
CHEVROLET3 (15%)
4
GMC2 (10%)
5
NISSAN1 (5%)
6
PONT1 (5%)
7
AUDI1 (5%)
8
VOLKSWAGEN1 (5%)
9
BUIC1 (5%)
10
FORD1 (5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Vehicle unit records

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

Sex Distribution (19 persons with recorded sex)

Male13 (68.4%)
-7.1%prior 14
Female6 (31.6%)
-40.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 35 mph speed zones increased from 5 in November 2022 to 6 in November 2023. Conversely, crashes in 65 mph speed zones saw a substantial decrease, falling from 5 to 1. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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: 2023-11-01 through 2023-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-11-01 through 2023-11-30 (30 days)
  • Geographic scope: MATTAPOISETT, MA
  • Total crash records analyzed: 14
  • Total persons involved: 22
  • Total vehicles involved: 20

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). "MATTAPOISETT, MA Crash Intelligence Report: November 2023." Published June 21, 2026. Reporting period: 2023-11-01 to 2023-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/mattapoisett/november-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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Mattapoisett, MA Crash Report — November 2023 | ThatCarHitMe.com