Monthly Traffic Safety Analysis

15 CRASHES IN
SANDWICH, MA
NOVEMBER 2023

All metrics benchmarked againstNovember 2022

Total crashes in SANDWICH, MA decreased by 53.1% year-over-year, from 32 in November 2022 to 15 in November 2023. The most notable shift was this substantial reduction in overall crash incidents. Fatalities remained at zero in both periods.

15

-53.1%was 32

Total Crash Events

0

Persons Killed

5

-28.6%was 7

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

The overall trend indicates a significant decline in crash incidents year-over-year. Total crashes decreased by 53.1%, falling from 32 in November 2022 to 15 in November 2023.

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 3.1% of total crashes in November 2022 to 6.7% in November 2023.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

5

Motorists Injured

Prior: 6-16.7%

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 peak day for crashes shifted from Tuesday, with 8 crashes in November 2022, to Thursday, with 6 crashes in November 2023. The peak crash hour also changed, moving from 5 PM (4 crashes) in November 2022 to 7 AM (3 crashes) in November 2023.

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 0 in both November 2022 and November 2023. The total number of injuries decreased from 7 in November 2022 to 5 in November 2023. The proportion of crashes resulting in "No Injury" decreased from 81.3% in November 2022 to 66.7% in November 2023, while "Minor Injury" crashes increased from a 9.4% share to a 13.3% share and "Possible Injury" crashes increased from a 6.3% share to a 13.3% share of total crashes.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes6.7%
Minor Injury2minor injury crashes13.3%
-33.3%prior 3
Possible Injury2possible injury crashes13.3%
0.0%prior 2
No Injury10no injury crashes66.7%
-61.5%prior 26

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

Crashes attributed to "No improper driving" decreased by 4, from 8 in November 2022 to 4 in November 2023. Incidents involving "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" decreased by 2, from 3 to 1. Conversely, crashes due to "Failed to yield right of way" increased by 1, from 1 to 2, while "Inattention" crashes remained stable at 4 in both periods.

Officer-Reported Primary Contributing Cause

No improper driving4 (26.7%)-50.0%prior 8
Inattention4 (26.7%)
Failed to yield right of way2 (13.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (6.7%)
Disregarded traffic signs, signals, road markings1 (6.7%)
Physical impairment1 (6.7%)
Exceeded authorized speed limit1 (6.7%)
Followed too closely1 (6.7%)

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 "Daylight" conditions decreased by 9, from 17 in November 2022 to 8 in November 2023. Incidents in "Dark - lighted roadway" decreased by 4, from 7 to 3, and those in "Dark - roadway not lighted" decreased by 3, from 5 to 2. Weather and road surface conditions data for November 2023 were not available for comparison.

Lighting

Daylight8 (53.3%)
-52.9%prior 17
Dark - lighted roadway3 (20.0%)
-57.1%prior 7
Dark - roadway not lighted2 (13.3%)
-60.0%prior 5
Dusk2 (13.3%)

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

Vehicles & Demographics

Top Vehicle Makes (24 vehicles)

1
TOYOTA6 (25%)
-25.0%prior 8
2
FORD4 (16.7%)
-60.0%prior 10
3
RAM3 (12.5%)
4
HONDA2 (8.3%)
-60.0%prior 5
5
CHEVROLET2 (8.3%)
6
SUBARU1 (4.2%)
7
VOLVO1 (4.2%)
8
GMC1 (4.2%)
9
JEEP1 (4.2%)
-83.3%prior 6
10
MERCEDES-BENZ1 (4.2%)

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 (34 persons with recorded sex)

Female18 (52.9%)
-51.4%prior 37
Male16 (47.1%)
-59.0%prior 39

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 in 30 mph zones decreased by 3, from 8 in November 2022 to 5 in November 2023. Crashes in 40 mph zones saw a decrease of 7, from 12 to 5. Additionally, crashes in 45 mph and 55 mph zones both decreased by 2, from 4 to 2 respectively. Fatalities remained at 0 across all speed zones in both periods.

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: SANDWICH, MA
  • Total crash records analyzed: 15
  • Total persons involved: 35
  • Total vehicles involved: 24

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). "SANDWICH, 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/sandwich/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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Sandwich, MA Crash Report — November 2023 | ThatCarHitMe.com