Yearly Traffic Safety Analysis

1,119 CRASHES IN
WEYMOUTH, MA
2023

All metrics benchmarked against2022

In 2023, Weymouth recorded 1,119 traffic crashes, a 1.8% decrease from the 1,140 crashes reported in 2022. While overall crashes declined slightly, the number of fatal crashes rose from zero in 2022 to three in 2023. The most significant year-over-year change was the increase in hit-and-run incidents, which grew from 10 in 2022 to 76 in 2023.

1,119

-1.8%was 1,140

Total Crash Events

3

Persons Killed

424

6.8%was 397

Persons Injured

76

660.0%was 10

Hit-and-Run Crashes

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 57 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume in Weymouth saw a slight year-over-year decrease of 1.8%, with 1,119 crashes in 2023 compared to 1,140 in 2022. Despite the drop in total incidents, the number of resulting injuries increased by 6.8% from 397 to 424. Additionally, there were three fatalities in 2023, whereas none were recorded in the prior year.

76

Hit-and-Run Crashes — 2023

660.0% vs prior (10)

The number of hit-and-run crashes increased significantly in 2023. There were 76 hit-and-run incidents, a substantial rise from the 10 recorded in 2022. This represents a 660% increase in the count of such crashes. Consequently, the hit-and-run rate as a percentage of total crashes grew from 0.9% in 2022 to 6.8% in 2023.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

0

Cyclists Killed

Prior: 00.0%

2

Motorists Killed

Prior: 0%

10

Pedestrians Injured

Prior: 911.1%

8

Cyclists Injured

Prior: 633.3%

406

Motorists Injured

Prior: 3816.6%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between the two years. In 2023, the peak day for crashes was Friday with 187 incidents, a change from Thursday (173 crashes) in 2022. The peak hour for crashes also shifted, moving from the 3 p.m. hour (103 crashes) in 2022 to the 5 p.m. hour (98 crashes) in 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased in 2023 compared to the previous year. Three fatal crashes were recorded in 2023, representing 0.3% of all incidents, up from zero fatal crashes in 2022. The proportion of serious injury crashes rose from 1.8% (20 crashes) to 2.0% (22 crashes), and minor injury crashes increased from 13.5% (154 crashes) to 15.6% (175 crashes). Consequently, the share of no-injury crashes decreased from 70.5% in 2022 to 68.9% in 2023.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.3%
Serious Injury22serious injury crashes2%
10.0%prior 20
Minor Injury175minor injury crashes15.6%
13.6%prior 154
Possible Injury91possible injury crashes8.1%
-14.2%prior 106
No Injury771no injury crashes68.9%
-4.1%prior 804

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors remained consistent, though their rankings and counts shifted. In 2023, 'Inattention' became the second most cited factor, with its count rising by 29.8% from 141 to 183 crashes. This displaced 'Failed to yield right of way,' which saw its count decrease by 14.0% from 178 to 153 crashes. Crashes attributed to an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' also increased in count from 47 to 59, a 25.5% rise.

Officer-Reported Primary Contributing Cause

No improper driving287 (25.6%)1.1%prior 284
Inattention183 (16.4%)29.8%prior 141
Failed to yield right of way153 (13.7%)-14.0%prior 178
Followed too closely114 (10.2%)-13.6%prior 132
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner59 (5.3%)25.5%prior 47
Failure to keep in proper lane or running off road58 (5.2%)-24.7%prior 77
Other improper action37 (3.3%)48.0%prior 25
Distracted24 (2.1%)-35.1%prior 37
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway21 (1.9%)50.0%prior 14
Driving too fast for conditions18 (1.6%)-18.2%prior 22

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Driving conditions for most crashes were similar year-over-year, with the majority occurring in 'Clear' weather (770 in 2023 vs. 787 in 2022) and on 'Dry' road surfaces (878 vs. 900). However, there was a notable increase in crashes on wet roads, rising from 175 in 2022 to 200 in 2023. Conversely, crashes on snowy roads decreased from 43 to 22. Lighting conditions remained stable, with 'Daylight' accounting for 765 crashes in both periods.

Weather

Clear770 (69.8%)
-2.2%prior 787
Rain96 (8.7%)
35.2%prior 71
Cloudy94 (8.5%)
-1.1%prior 95
Cloudy/Rain36 (3.3%)
12.5%prior 32
Snow16 (1.5%)
-30.4%prior 23
Rain/Cloudy15 (1.4%)
25.0%prior 12
Clear/Other13 (1.2%)
-38.1%prior 21
Clear/Unknown12 (1.1%)
-58.6%prior 29
Clear/Cloudy11 (1.0%)
37.5%prior 8
Snow/Sleet, hail (freezing rain or drizzle)9 (0.8%)
12.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight765 (68.5%)
0.0%prior 765
Dark - lighted roadway257 (23.0%)
-3.4%prior 266
Dark - roadway not lighted38 (3.4%)
-9.5%prior 42
Dusk31 (2.8%)
-3.1%prior 32
Dawn20 (1.8%)
-4.8%prior 21
Dark - unknown roadway lighting5 (0.4%)
-16.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry878 (78.7%)
-2.4%prior 900
Wet200 (17.9%)
14.3%prior 175
Snow22 (2.0%)
-48.8%prior 43
Ice10 (0.9%)
-23.1%prior 13
Slush5 (0.4%)
-16.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The distribution of vehicle makes involved in crashes remained largely unchanged, with Toyota, Ford, and Honda being the top three most common makes in both 2023 and 2022. Analysis of persons involved shows a shift in age demographics. The number of individuals in the 16-20 age group involved in crashes increased from 218 to 258. In contrast, involvement for the 21-25 and 26-34 age groups saw decreases.

Top Vehicle Makes (2,122 vehicles)

1
TOYOTA374 (17.6%)
0.8%prior 371
2
FORD244 (11.5%)
-7.2%prior 263
3
HONDA236 (11.1%)
4.9%prior 225
4
CHEVROLET211 (9.9%)
4.5%prior 202
5
NISSAN148 (7%)
-1.3%prior 150
6
JEEP135 (6.4%)
-4.3%prior 141
7
SUBARU70 (3.3%)
40.0%prior 50
8
HYUNDAI61 (2.9%)
-29.9%prior 87
9
KIA46 (2.2%)
-20.7%prior 58
10
VOLKSWAGEN44 (2.1%)
25.7%prior 35

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (2,404 persons with recorded sex)

Male1,281 (53.3%)
-3.0%prior 1,321
Female1,123 (46.7%)
-0.8%prior 1,132

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones shifted between the two years. Crashes in 30 mph zones increased from 499 to 528, while those in 35 mph zones decreased from 272 to 218. Crashes in 60 mph zones also saw an increase from 90 to 104. All three fatal crashes in 2023 occurred in these zones, with one in a 30 mph zone and two in 60 mph zones, compared to zero fatal crashes in 2022.

Fatal crashes by zone: 30 mph: 1 of 528 (0.189%) · 60 mph: 2 of 104 (1.923%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: WEYMOUTH, MA
  • Total crash records analyzed: 1,119
  • Total persons involved: 2,631
  • Total vehicles involved: 2,122

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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/weymouth/2023-annual-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 — 2023 | ThatCarHitMe.com