Monthly Traffic Safety Analysis

87 CRASHES IN
WEYMOUTH, MA
NOVEMBER 2023

All metrics benchmarked againstNovember 2022

In November 2023, WEYMOUTH experienced 87 crashes, a 20.9% decrease compared to the 110 crashes recorded in November 2022. Despite the overall reduction in crashes, serious injury crashes increased significantly from 1 to 5 incidents. This marks a notable shift in crash outcomes year-over-year.

87

-20.9%was 110

Total Crash Events

0

Persons Killed

34

Persons Injured

6

100.0%was 3

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

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 decrease in total crashes, with 87 incidents in November 2023 compared to 110 in November 2022, representing a 20.9% reduction. Total injuries remained stable at 34 in both periods. This suggests a notable decline in the frequency of crash events.

6

Hit-and-Run Crashes — November 2023

100.0% vs prior (3)

Hit-and-run crashes increased from 3 in November 2022 to 6 in November 2023, marking a 100% increase in count. Consequently, the hit-and-run rate rose from 2.7% of total crashes to 6.9% of total crashes. This indicates an upward trend in hit-and-run incidents year-over-year.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

33

Motorists Injured

Prior: 323.1%

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

Wednesday remained the peak day for crashes in both periods, though the count decreased from 29 in November 2022 to 20 in November 2023. The peak hour for crashes shifted from 5 PM, with 12 incidents in the prior period, to 2 PM, with 9 incidents 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

There were no fatalities or fatal crashes reported in either November 2022 or November 2023. However, serious injury crashes increased from 1 (0.9% share of crashes) in the prior period to 5 (5.7% share of crashes) in the current period, a 400% increase in count. Conversely, minor injury crashes decreased from 13 to 9, and possible injury crashes decreased from 10 to 8.

Outcome by Severity (Crash Events)

Serious Injury5serious injury crashes5.7%
400.0%prior 1
Minor Injury9minor injury crashes10.3%
-30.8%prior 13
Possible Injury8possible injury crashes9.2%
-20.0%prior 10
No Injury61no injury crashes70.1%
-25.6%prior 82

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 from 34 to 25, a 26.5% reduction in count, maintaining a similar share of total crashes (30.9% vs 28.7%). 'Failed to yield right of way' crashes decreased from 17 to 13, a 23.5% reduction in count. 'Inattention' crashes saw a slight increase from 14 to 15, a 7.1% increase in count, and its share of crashes rose from 12.7% to 17.2%.

Officer-Reported Primary Contributing Cause

No improper driving25 (28.7%)-26.5%prior 34
Inattention15 (17.2%)7.1%prior 14
Failed to yield right of way13 (14.9%)-23.5%prior 17
Followed too closely7 (8%)-46.2%prior 13
Failure to keep in proper lane or running off road4 (4.6%)-60.0%prior 10
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (3.4%)-40.0%prior 5
Operating defective equipment3 (3.4%)
Other improper action2 (2.3%)
Disregarded traffic signs, signals, road markings2 (2.3%)
Visibility obstructed2 (2.3%)

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 under clear weather conditions decreased from 79 to 61 year-over-year. Similarly, crashes on dry road surfaces decreased from 98 to 74. Crashes in daylight conditions decreased from 62 to 53, while those in dark-lighted roadway conditions decreased from 32 to 29. The number of crashes on wet roads increased from 11 to 13.

Weather

Clear61 (70.9%)
-22.8%prior 79
Cloudy6 (7.0%)
-40.0%prior 10
Clear/Unknown4 (4.7%)
-20.0%prior 5
Rain4 (4.7%)
-50.0%prior 8
Cloudy/Rain4 (4.7%)
Cloudy/Other2 (2.3%)
Rain/Unknown1 (1.2%)
Clear/Other1 (1.2%)
Cloudy/Unknown1 (1.2%)
Rain/Clear1 (1.2%)

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

Lighting

Daylight53 (60.9%)
-14.5%prior 62
Dark - lighted roadway29 (33.3%)
-9.4%prior 32
Dark - roadway not lighted2 (2.3%)
-75.0%prior 8
Dawn2 (2.3%)
Dusk1 (1.1%)
-80.0%prior 5

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

Road Surface

Dry74 (85.1%)
-24.5%prior 98
Wet13 (14.9%)
18.2%prior 11

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

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 212 in November 2022 to 163 in November 2023. Toyota remained the top vehicle make involved, though its count decreased from 41 to 30. The 16-20 age group saw an increase in persons involved from 20 to 25, while the 55-64 age group experienced a decrease from 43 to 19 persons.

Top Vehicle Makes (163 vehicles)

1
TOYOTA30 (18.4%)
-26.8%prior 41
2
FORD22 (13.5%)
15.8%prior 19
3
CHEVROLET15 (9.2%)
-25.0%prior 20
4
HONDA13 (8%)
-40.9%prior 22
5
JEEP9 (5.5%)
50.0%prior 6
6
NISSAN9 (5.5%)
-25.0%prior 12
7
BMW7 (4.3%)
8
GMC6 (3.7%)
9
DODGE6 (3.7%)
-25.0%prior 8
10
SUBARU5 (3.1%)
-16.7%prior 6

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

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

Sex Distribution (176 persons with recorded sex)

Male97 (55.1%)
-24.2%prior 128
Female79 (44.9%)
-26.9%prior 108

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 30 mph zones decreased from 46 to 40. Crashes in 35 mph zones decreased from 30 to 21, and those in 60 mph zones decreased from 11 to 8. There were no fatal crashes reported in any speed zone for either the current or prior 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: WEYMOUTH, MA
  • Total crash records analyzed: 87
  • Total persons involved: 196
  • 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). "WEYMOUTH, 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/weymouth/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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Weymouth, MA Crash Report — November 2023 | ThatCarHitMe.com