Yearly Traffic Safety Analysis

1,125 CRASHES IN
WEYMOUTH, MA
2024

All metrics benchmarked against2023

In 2024, Weymouth recorded 1,125 total vehicle crashes, a slight increase of 0.5% from the 1,119 crashes recorded in 2023. While overall crash volume remained stable, incidents involving pedestrians saw a notable year-over-year increase of 64.3%, rising from 14 to 23. Concurrently, total fatalities decreased from 3 to 2, and total injuries fell by 1.9%.

1,125

0.5%was 1,119

Total Crash Events

2

-33.3%was 3

Persons Killed

416

-1.9%was 424

Persons Injured

103

35.5%was 76

Hit-and-Run Crashes

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 55 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in Weymouth remained relatively stable year-over-year, with total crashes increasing by a marginal 0.5% from 1,119 in 2023 to 1,125 in 2024. Despite the slight rise in total incidents, the number of resulting injuries decreased by 1.9% from 424 to 416. Fatalities also declined, falling from 3 in the prior year to 2 in the current year.

103

Hit-and-Run Crashes — 2024

35.5% vs prior (76)

Hit-and-run incidents increased significantly in 2024 compared to the previous year. The total number of hit-and-run crashes rose from 76 in 2023 to 103 in 2024, representing a 35.5% increase in count. This pushed the hit-and-run rate, or the percentage of total crashes that were hit-and-runs, up from 6.8% to 9.2%.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 10.0%

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 2-50.0%

0

Other Killed

Prior: 00.0%

21

Pedestrians Injured

Prior: 10110.0%

11

Cyclists Injured

Prior: 837.5%

380

Motorists Injured

Prior: 406-6.4%

4

Other Injured

Prior: 0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes shifted between the two periods. In 2024, the peak day for crashes was Saturday with 179 incidents, a change from 2023 when Friday was the peak day with 187 crashes. Similarly, the peak hour for collisions moved earlier in the day, from the 5 p.m. hour in 2023 (98 crashes) to the 2 p.m. hour in 2024 (89 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes saw a slight reduction year-over-year. The fatal crash rate decreased from 0.27 per 100 crashes in 2023 to 0.18 in 2024, corresponding to a drop from 3 to 2 fatal incidents. While the overall proportion of crashes involving any injury remained stable at approximately 25.7%, there was a shift within injury categories; the share of minor injury crashes increased from 15.6% to 16.9%, while the share of serious injury crashes decreased from 2.0% to 1.7%.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.2%
-33.3%prior 3
Serious Injury19serious injury crashes1.7%
-13.6%prior 22
Minor Injury190minor injury crashes16.9%
8.6%prior 175
Possible Injury80possible injury crashes7.1%
-12.1%prior 91
No Injury779no injury crashes69.2%
1.0%prior 771

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

The ranking of top contributing factors shifted between periods, with 'Failed to yield right of way' moving from the third to the second most common factor. The count of crashes attributed to failing to yield increased by 44.4%, from 153 incidents in 2023 to 221 in 2024. In contrast, crashes linked to 'Inattention' decreased in count by 6.0% (from 183 to 172), while those involving 'Followed too closely' rose by 9.6% (from 114 to 125).

Officer-Reported Primary Contributing Cause

No improper driving262 (23.3%)-8.7%prior 287
Failed to yield right of way221 (19.6%)44.4%prior 153
Inattention172 (15.3%)-6.0%prior 183
Followed too closely125 (11.1%)9.6%prior 114
Failure to keep in proper lane or running off road54 (4.8%)-6.9%prior 58
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner38 (3.4%)-35.6%prior 59
Disregarded traffic signs, signals, road markings21 (1.9%)50.0%prior 14
Visibility obstructed20 (1.8%)17.6%prior 17
Other improper action17 (1.5%)-54.1%prior 37
Driving too fast for conditions13 (1.2%)-27.8%prior 18

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained broadly similar year-over-year, with the vast majority of incidents in both periods occurring during daylight on dry roads. In 2024, the proportion of crashes in clear weather increased, accounting for 74.5% of all incidents compared to 68.8% in 2023. Correspondingly, the share of crashes on wet road surfaces decreased from 17.9% in 2023 to 15.8% in 2024.

Weather

Clear838 (75.1%)
8.8%prior 770
Rain99 (8.9%)
3.1%prior 96
Cloudy68 (6.1%)
-27.7%prior 94
Cloudy/Rain21 (1.9%)
-41.7%prior 36
Clear/Other14 (1.3%)
7.7%prior 13
Reported but invalid11 (1.0%)
Rain/Cloudy10 (0.9%)
-33.3%prior 15
Clear/Clear10 (0.9%)
Snow9 (0.8%)
-43.8%prior 16
Clear/Cloudy8 (0.7%)
-27.3%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight781 (69.9%)
2.1%prior 765
Dark - lighted roadway239 (21.4%)
-7.0%prior 257
Dark - roadway not lighted46 (4.1%)
21.1%prior 38
Dusk29 (2.6%)
-6.5%prior 31
Dawn20 (1.8%)
0.0%prior 20
Dark - unknown roadway lighting2 (0.2%)
-60.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry922 (82.7%)
5.0%prior 878
Wet178 (16.0%)
-11.0%prior 200
Snow7 (0.6%)
-68.2%prior 22
Ice3 (0.3%)
-70.0%prior 10
Slush2 (0.2%)
-60.0%prior 5
Other2 (0.2%)
Sand, mud, dirt, oil, gravel1 (0.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The top five vehicle makes involved in crashes—Toyota, Ford, Honda, Chevrolet, and Nissan—were identical in both 2023 and 2024, with Toyota remaining the most common make in both periods. The number of Toyotas in crashes increased from 374 to 405, while Chevrolet involvement decreased from 211 to 176. The age distribution of persons involved in crashes was also consistent, with the 26-34 age group being the largest in both years, accounting for 449 individuals in 2023 and 443 in 2024.

Top Vehicle Makes (2,226 vehicles)

1
TOYOTA405 (18.2%)
8.3%prior 374
2
FORD247 (11.1%)
1.2%prior 244
3
HONDA228 (10.2%)
-3.4%prior 236
4
CHEVROLET176 (7.9%)
-16.6%prior 211
5
NISSAN150 (6.7%)
1.4%prior 148
6
JEEP137 (6.2%)
1.5%prior 135
7
HYUNDAI81 (3.6%)
32.8%prior 61
8
SUBARU80 (3.6%)
14.3%prior 70
9
KIA57 (2.6%)
23.9%prior 46
10
GMC46 (2.1%)
12.2%prior 41

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (2,456 persons with recorded sex)

Male1,339 (54.5%)
4.5%prior 1,281
Female1,117 (45.5%)
-0.5%prior 1,123

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

Analysis of crashes by speed zone indicates a shift in incident locations between the two years. Crashes occurring in 30 mph zones decreased from 528 in 2023 to 448 in 2024. Conversely, crashes in 35 mph zones increased from 218 to 273 over the same period. Fatal crashes also occurred in different zones; in 2023, fatalities were recorded in 30 mph and 60 mph zones, whereas in 2024, they occurred in 35 mph and 60 mph zones.

Fatal crashes by zone: 35 mph: 1 of 273 (0.366%) · 60 mph: 1 of 94 (1.064%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: WEYMOUTH, MA
  • Total crash records analyzed: 1,125
  • Total persons involved: 2,782
  • Total vehicles involved: 2,226

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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/weymouth/2024-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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