Monthly Traffic Safety Analysis

10 CRASHES IN
MATTAPOISETT, MA
JULY 2023

All metrics benchmarked againstJuly 2022

Total crashes in MATTAPOISETT decreased by 16.67%, from 12 in July 2022 to 10 in July 2023. Despite this overall reduction, total injuries remained constant at 4 for both periods. A notable shift includes the absence of serious injury crashes in the current period, which accounted for 1 crash in the prior year.

10

-16.7%was 12

Total Crash Events

0

Persons Killed

4

Persons Injured

0

-100.0%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. 1 crash with unreported severity is 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, crashes in MATTAPOISETT decreased year-over-year, with total crashes falling by 16.67% from 12 in July 2022 to 10 in July 2023. Total fatalities remained at 0 in both periods, and total injuries also held steady at 4. This indicates a reduction in crash frequency without a corresponding change in the total number of injured persons.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

4

Motorists Injured

Prior: 333.3%

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 Sunday, with 4 crashes in July 2022, to Friday, with 3 crashes in July 2023. Similarly, the peak hour for crashes moved from 5 p.m. in the prior period (2 crashes) to 3 p.m. in the current period (2 crashes). Crashes on Sundays completely disappeared in the current period, while crashes on Fridays increased from 1 to 3.

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

The total number of injuries remained constant at 4 for both July 2022 and July 2023. However, the distribution of injury severity changed, with serious injury crashes (1 crash, 8.3% of total) reported in July 2022 being absent in July 2023. Conversely, minor injury crashes increased from 1 (8.3% of total) in the prior period to 3 (30% of total) in the current period.

Outcome by Severity (Crash Events)

Minor Injury3minor injury crashes30%
200.0%prior 1
No Injury6no injury crashes60%
-25.0%prior 8

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

Crashes attributed to "No improper driving" decreased by 1, from 4 in July 2022 to 3 in July 2023, representing a 25% reduction in count. Crashes linked to "Inattention" also decreased by 1, from 2 to 1, a 50% reduction in count. The factor "History heart/epilepsy/fainting" appeared in the current period with 2 crashes, while factors like "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" and "Followed too closely," each contributing to 1 crash in the prior period, were not present in the current data.

Officer-Reported Primary Contributing Cause

No improper driving3 (30%)
Failed to yield right of way2 (20%)
History heart/epilepsy/fainting2 (20%)
Inattention1 (10%)
Other improper action1 (10%)

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 decreased from 11 in July 2022 to 8 in July 2023. Similarly, crashes during "Daylight" conditions saw a reduction from 11 to 7 year-over-year. There was a shift in dark lighting conditions, with 1 crash reported in "Dark - lighted roadway" in the prior period, compared to 2 crashes in "Dark - roadway not lighted" in the current period.

Weather

Clear8 (88.9%)
-27.3%prior 11
Cloudy1 (11.1%)

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

Lighting

Daylight7 (77.8%)
-36.4%prior 11
Dark - roadway not lighted2 (22.2%)

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

Vehicles & Demographics

Top Vehicle Makes (15 vehicles)

1
TOYOTA4 (26.7%)
2
HONDA3 (20%)
3
GMC2 (13.3%)
4
LINC1 (6.7%)
5
MAZDA1 (6.7%)
6
SUBARU1 (6.7%)
7
JEEP1 (6.7%)
-83.3%prior 6
8
FORD1 (6.7%)
9
CHEVROLET1 (6.7%)

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

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

Sex Distribution (12 persons with recorded sex)

Female6 (50.0%)
-45.5%prior 11
Male6 (50.0%)
-40.0%prior 10

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

Crashes occurring in 25 mph zones decreased from 3 in July 2022 to 2 in July 2023, while crashes in 40 mph zones remained stable at 2 for both periods. The current period introduced crashes in 35 mph (2 crashes) and 65 mph (4 crashes) zones, which were not present in the prior year's data. Conversely, crashes in 20 mph (1 crash), 30 mph (1 crash), 45 mph (3 crashes), and 50 mph (2 crashes) zones from the prior period were not observed in the current period.

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: MATTAPOISETT, MA
  • Total crash records analyzed: 10
  • Total persons involved: 16
  • Total vehicles involved: 15

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: 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/mattapoisett/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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Mattapoisett, MA Crash Report — July 2023 | ThatCarHitMe.com