Monthly Traffic Safety Analysis

111 CRASHES IN
WEYMOUTH, MA
JUNE 2023

All metrics benchmarked againstJune 2022

Total crashes in WEYMOUTH, MA increased by 12.12% from 99 in June 2022 to 111 in June 2023. While total injuries saw a slight decrease from 41 to 40, a notable shift was the increase in hit-and-run crashes from 0 in the prior period to 8 in the current period. Fatalities remained at 0 in both periods.

111

12.1%was 99

Total Crash Events

0

Persons Killed

40

-2.4%was 41

Persons Injured

8

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 · 2023-06-01 to 2023-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the trend indicates a rise in total crashes, increasing from 99 to 111, which is a 12.12% increase year-over-year. Despite this increase in crash volume, total injuries slightly decreased by 2.44%, from 41 to 40. Fatalities remained stable at 0 for both periods.

8

Hit-and-Run Crashes — June 2023

7.2% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 10.0%

2

Cyclists Injured

Prior: 1100.0%

37

Motorists Injured

Prior: 39-5.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns for crashes shifted year-over-year, with the peak day changing from Wednesday (23 crashes) in June 2022 to Friday (21 crashes) in June 2023. Similarly, the peak hour for crashes moved from 5 PM (11 crashes) in the prior period to 3 PM (13 crashes) in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution shows a decrease in serious injury crashes from 2 (2%) in June 2022 to 1 (0.9%) in June 2023. Minor injury crashes increased significantly from 9 (9.1%) to 17 (15.3%), while possible injury crashes decreased from 19 (19.2%) to 14 (12.6%). No fatal crashes were recorded in either period.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes0.9%
-50.0%prior 2
Minor Injury17minor injury crashes15.3%
88.9%prior 9
Possible Injury14possible injury crashes12.6%
-26.3%prior 19
No Injury73no injury crashes65.8%
10.6%prior 66

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'No improper driving' increased from 26 crashes to 35 crashes, a 34.6% increase in count, maintaining its top position. 'Inattention' also saw a substantial rise, from 13 crashes to 20 crashes, a 53.8% increase in count. The top four contributing factors remained consistent in ranking between the two periods.

Officer-Reported Primary Contributing Cause

No improper driving35 (31.5%)34.6%prior 26
Inattention20 (18%)53.8%prior 13
Failed to yield right of way14 (12.6%)16.7%prior 12
Followed too closely13 (11.7%)30.0%prior 10
Failure to keep in proper lane or running off road6 (5.4%)-14.3%prior 7
Other improper action5 (4.5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (2.7%)-40.0%prior 5
Over-correcting/over-steering2 (1.8%)
Made an improper turn1 (0.9%)
Distracted1 (0.9%)-80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Adverse weather conditions, including 'Cloudy', 'Rain', 'Cloudy/Rain', and 'Rain/Cloudy', collectively increased from 9 crashes in June 2022 to 30 crashes in June 2023. Crashes occurring on wet road surfaces more than doubled, rising from 9 in the prior period to 19 in the current period. Crashes under daylight conditions increased from 85 to 96, while those in dark conditions with lighted roadways increased from 8 to 12.

Weather

Clear72 (66.7%)
-15.3%prior 85
Cloudy14 (13.0%)
Rain8 (7.4%)
Cloudy/Rain6 (5.6%)
Rain/Cloudy2 (1.9%)
Clear/Cloudy2 (1.9%)
Clear/Other2 (1.9%)
Cloudy/Other1 (0.9%)
Cloudy/Cloudy1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Weather condition at time of crash

Lighting

Daylight96 (86.5%)
12.9%prior 85
Dark - lighted roadway12 (10.8%)
50.0%prior 8
Dark - roadway not lighted2 (1.8%)
Dawn1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Lighting condition field

Road Surface

Dry92 (82.9%)
2.2%prior 90
Wet19 (17.1%)
111.1%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Road surface condition field

Vehicles & Demographics

Toyota remained the most common vehicle make involved in crashes, increasing from 35 vehicles in June 2022 to 46 in June 2023. Ford and Chevrolet, while still prominent, saw their crash involvement counts decrease from 25 to 21 and 22 to 19 respectively. Among persons involved, the 26-34 age group saw an increase from 35 to 45, and the 35-44 age group increased from 25 to 43, while the 16-20 age group decreased from 32 to 21.

Top Vehicle Makes (220 vehicles)

1
TOYOTA46 (20.9%)
31.4%prior 35
2
FORD21 (9.5%)
-16.0%prior 25
3
CHEVROLET19 (8.6%)
-13.6%prior 22
4
HONDA18 (8.2%)
12.5%prior 16
5
JEEP16 (7.3%)
6.7%prior 15
6
NISSAN15 (6.8%)
7
SUBARU12 (5.5%)
140.0%prior 5
8
HYUNDAI7 (3.2%)
0.0%prior 7
9
MERCEDES-BENZ5 (2.3%)
10
MAZDA5 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Vehicle unit records

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

Sex Distribution (240 persons with recorded sex)

Male127 (52.9%)
0.0%prior 127
Female113 (47.1%)
18.9%prior 95

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones increased from 43 to 56, while crashes in 35 mph zones decreased from 21 to 15. A notable increase was observed in 60 mph zones, where crashes doubled from 8 to 16. No fatalities were recorded across any speed zone in either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · 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: 2023-06-01 through 2023-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-06-01 through 2023-06-30 (30 days)
  • Geographic scope: WEYMOUTH, MA
  • Total crash records analyzed: 111
  • Total persons involved: 268
  • Total vehicles involved: 220

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: June 2023." Published June 21, 2026. Reporting period: 2023-06-01 to 2023-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/weymouth/june-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 — June 2023 | ThatCarHitMe.com