Monthly Traffic Safety Analysis

74 CRASHES IN
WEYMOUTH, MA
MARCH 2023

All metrics benchmarked againstMarch 2022

In March 2023, WEYMOUTH experienced 74 crashes, a 10.8% decrease from the 83 crashes recorded in March 2022. A notable shift was the absence of serious injuries in March 2023, compared to 2 serious injuries in the prior year. Additionally, hit-and-run crashes increased from 0 in March 2022 to 3 in March 2023.

74

-10.8%was 83

Total Crash Events

0

Persons Killed

23

-23.3%was 30

Persons Injured

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a decrease in crash incidents year-over-year. Total crashes fell by 10.8%, from 83 in March 2022 to 74 in March 2023. Concurrently, total injuries decreased by 23.3%, from 30 in March 2022 to 23 in March 2023.

3

Hit-and-Run Crashes — March 2023

4.1% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

23

Motorists Injured

Prior: 30-23.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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 in March 2022 (15 crashes) to Wednesday in March 2023 (15 crashes). The peak hour also changed, moving from 5 p.m. with 10 crashes in March 2022 to 3 p.m. with 8 crashes in March 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities in either March 2023 or March 2022. Serious injuries (Severity A) decreased from 2 in March 2022 to 0 in March 2023. Minor injuries (Severity B) increased from 8 to 12, while possible injuries (Severity C) decreased from 8 to 4.

Outcome by Severity (Crash Events)

Minor Injury12minor injury crashes16.2%
50.0%prior 8
Possible Injury4possible injury crashes5.4%
-50.0%prior 8
No Injury52no injury crashes70.3%
-11.9%prior 59

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Most severe injury per crash record

Top Contributing Factors

The count of crashes attributed to 'Failed to yield right of way' decreased significantly by 13 crashes, from 23 in March 2022 to 10 in March 2023, representing a 56.5% reduction. 'No improper driving' remained stable at 16 crashes in both periods. 'Followed too closely' crashes increased by 1, from 10 to 11, while 'Inattention' crashes decreased by 2, from 10 to 8.

Officer-Reported Primary Contributing Cause

No improper driving16 (21.6%)0.0%prior 16
Followed too closely11 (14.9%)10.0%prior 10
Failed to yield right of way10 (13.5%)-56.5%prior 23
Inattention8 (10.8%)-20.0%prior 10
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (5.4%)
Other improper action4 (5.4%)
Failure to keep in proper lane or running off road3 (4.1%)-70.0%prior 10
Made an improper turn3 (4.1%)
Distracted2 (2.7%)
Over-correcting/over-steering2 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 57 in March 2022 to 54 in March 2023, while crashes in rainy conditions increased from 2 to 5. Daylight crashes decreased from 62 to 58, and crashes in dark-lighted roadway conditions decreased from 17 to 13. Crashes on dry road surfaces decreased from 67 to 60, and on wet surfaces from 15 to 12.

Weather

Clear54 (75.0%)
-5.3%prior 57
Cloudy6 (8.3%)
20.0%prior 5
Rain5 (6.9%)
Rain/Snow2 (2.8%)
Clear/Rain1 (1.4%)
Clear/Cloudy1 (1.4%)
Rain/Cloudy1 (1.4%)
Snow/Sleet, hail (freezing rain or drizzle)1 (1.4%)
Cloudy/Unknown1 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Weather condition at time of crash

Lighting

Daylight58 (78.4%)
-6.5%prior 62
Dark - lighted roadway13 (17.6%)
-23.5%prior 17
Dusk2 (2.7%)
Dark - unknown roadway lighting1 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Lighting condition field

Road Surface

Dry60 (81.1%)
-10.4%prior 67
Wet12 (16.2%)
-20.0%prior 15
Slush1 (1.4%)
Snow1 (1.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 159 in March 2022 to 138 in March 2023. Among top makes, FORD-involved crashes decreased by 8 (from 24 to 16), while HONDA-involved crashes increased by 3 (from 13 to 16). In terms of persons involved, the 26-34 age group saw a decrease of 14 persons (from 38 to 24), and the 55-64 age group saw a decrease of 15 persons (from 36 to 21).

Top Vehicle Makes (138 vehicles)

1
TOYOTA27 (19.6%)
-10.0%prior 30
2
HONDA16 (11.6%)
23.1%prior 13
3
FORD16 (11.6%)
-33.3%prior 24
4
CHEVROLET15 (10.9%)
-6.3%prior 16
5
JEEP13 (9.4%)
8.3%prior 12
6
NISSAN10 (7.2%)
-28.6%prior 14
7
HYUNDAI6 (4.3%)
8
VOLKSWAGEN4 (2.9%)
-20.0%prior 5
9
BMW4 (2.9%)
10
KIA4 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Vehicle unit records

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

Sex Distribution (154 persons with recorded sex)

Female79 (51.3%)
-16.0%prior 94
Male75 (48.7%)
-28.6%prior 105

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones remained stable at 38 crashes in both March 2023 and March 2022. Crashes in 35 mph zones decreased significantly from 29 in March 2022 to 9 in March 2023, a 69.0% reduction. Conversely, crashes in 40 mph zones increased from 6 to 10. Additionally, March 2023 reported 3 crashes in 20 mph zones and 1 crash in 50 mph zones, categories not present in the March 2022 data.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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: 2023-03-01 through 2023-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-03-01 through 2023-03-31 (31 days)
  • Geographic scope: WEYMOUTH, MA
  • Total crash records analyzed: 74
  • Total persons involved: 166
  • Total vehicles involved: 138

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: March 2023." Published June 21, 2026. Reporting period: 2023-03-01 to 2023-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/weymouth/march-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 — March 2023 | ThatCarHitMe.com