ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WEYMOUTH, MA · NOVEMBER 2024
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/weymouth/november-2024-report
Monthly Traffic Safety Analysis
99 CRASHES IN
WEYMOUTH, MA
NOVEMBER 2024
In November 2024, the city of WEYMOUTH experienced 99 crashes, an increase from 87 crashes in November 2023. This represents a 13.79% rise in total crash incidents year-over-year. The most notable shift was the increase in fatalities, from 0 in the prior period to 1 in the current period.
99
▲ 13.8%was 87
Total Crash Events
1
Persons Killed
27
▼ -20.6%was 34
Persons Injured
7
▲ 16.7%was 6
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 11 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in WEYMOUTH showed an upward trend, increasing by 13.79% from 87 crashes in November 2023 to 99 crashes in November 2024. Fatalities increased from 0 to 1, while total injuries decreased by 20.59%, from 34 to 27.
7
Hit-and-Run Crashes — November 2024
▲ 16.7% vs prior (6)
Hit-and-run crashes increased from 6 incidents in November 2023 to 7 incidents in November 2024. The hit-and-run rate also saw a slight increase, moving from 6.9% of total crashes to 7.1% of total crashes, indicating a marginal upward trend.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Motorists Killed
2
Pedestrians Injured
25
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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 Wednesday with 20 incidents in November 2023 to Thursday with 18 incidents in November 2024. Similarly, the peak hour for crashes moved from 2 PM with 9 incidents in the prior period to 5 PM with 10 incidents in the current period, indicating a shift in temporal crash patterns.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The fatal crash rate increased from 0% in November 2023 to 1.01% in November 2024, with one fatal crash recorded in the current period. The proportion of serious injury crashes decreased from 5.7% of total crashes (5 incidents) in the prior period to 2% (2 incidents) in the current period, despite a slight decrease in overall injury crashes from 22 to 20.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'Failed to yield right of way' saw a significant increase of 84.6% in count, rising from 13 crashes to 24 crashes, making it the top factor in the current period. Conversely, 'No improper driving' decreased by 24% in count, from 25 crashes to 19 crashes, and 'Inattention' decreased by 33.3% in count, from 15 crashes to 10 crashes. 'Followed too closely' increased by 42.9% in count, from 7 crashes to 10 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 61 to 67, while those in rainy conditions increased from 4 to 12. Crashes on wet road surfaces also increased from 13 to 19. Incidents occurring in daylight decreased from 53 to 49, whereas crashes in dark conditions with lighted roadways increased from 29 to 37.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 163 in November 2023 to 226 in November 2024. Toyota remained the most frequently involved vehicle make, with its count rising from 30 to 41, and Honda moved from the fourth to the second most common make, increasing from 13 to 26 vehicles. The 35-44 age group saw a notable increase in persons involved, from 23 to 44, while the 65+ age group decreased from 32 to 29 persons.
Top Vehicle Makes (226 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Vehicle unit records
69 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (212 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone decreased from 40 to 36. Conversely, crashes in the 35 mph zone increased from 21 to 29, and this zone recorded the only fatal crash in the current period, resulting in a 3.448% fatal rate for that zone. Crashes in the 40 mph zone increased from 6 to 11, while those in the 60 mph zone decreased from 8 to 5.
Fatal crashes by zone: 35 mph: 1 of 29 (3.448%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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: 2024-11-01 through 2024-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-11-01 through 2024-11-30 (30 days)
- Geographic scope: WEYMOUTH, MA
- Total crash records analyzed: 99
- Total persons involved: 285
- Total vehicles involved: 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: November 2024." Published June 21, 2026. Reporting period: 2024-11-01 to 2024-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/weymouth/november-2024-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2024-11-01 – 2024-11-30
Generated: June 21, 2026 · All rights reserved