ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · PLYMOUTH, MA · APRIL 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/plymouth/april-2024-report
Monthly Traffic Safety Analysis
51 CRASHES IN
PLYMOUTH, MA
APRIL 2024
In April 2024, Plymouth experienced a notable decrease in traffic incidents compared to April 2023, with total crashes falling from 65 to 51, representing a 21.5% reduction. This period also saw a significant 47.8% decrease in total injuries, dropping from 23 to 12. A prominent shift was the 60% reduction in DUI crashes, which decreased from 5 to 2.
51
▼ -21.5%was 65
Total Crash Events
0
Persons Killed
12
▼ -47.8%was 23
Persons Injured
1
▼ -50.0%was 2
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash data for April shows a downward trend year-over-year, with total crashes decreasing by 21.5% from 65 in April 2023 to 51 in April 2024. Total injuries also saw a substantial decline, dropping by 47.8% from 23 to 12. Fatalities remained stable at 0 for both periods.
1
Hit-and-Run Crashes — April 2024
▼ -50.0% vs prior (2)
Hit-and-run crashes decreased by 50% year-over-year, falling from 2 incidents in April 2023 to 1 in April 2024. Consequently, the hit-and-run rate decreased from 3.1% of all crashes to 2%.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
11
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · 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 Monday in April 2023 (12 crashes) to Sunday in April 2024 (12 crashes). The peak hour also changed, moving from 2 PM with 9 crashes in the prior period to 12 PM with 6 crashes in the current period. This indicates a shift in the busiest times for traffic incidents.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The number of fatal crashes remained at 0 in both April 2023 and April 2024. Total injuries decreased significantly by 47.8%, from 23 to 12. Serious injury crashes (severity A) decreased from 2 to 1, while possible injury crashes (severity C) saw a 66.7% reduction, falling from 6 to 2.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Most severe injury per crash record
Top Contributing Factors
Several key contributing factors saw decreases in count year-over-year. Crashes attributed to 'Failed to yield right of way' decreased by 44.4%, from 9 in April 2023 to 5 in April 2024. 'Inattention' related crashes decreased from 14 to 11, a 21.4% reduction, while 'Followed too closely' crashes decreased from 5 to 4, a 20% reduction in count. The top three contributing factors remained 'Inattention', 'No improper driving', and 'Failed to yield right of way' in both periods, though their counts decreased.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions decreased from 49 in April 2023 to 27 in April 2024, a 44.9% reduction, leading to a decrease in their share of total crashes from 75.4% to 52.9%. Conversely, crashes on wet road surfaces doubled from 9 to 18, increasing their share from 13.8% to 35.3%. Crashes during dark conditions with unlighted roadways increased from 4 to 6, a 50% rise.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 109 to 79, a 27.5% reduction, consistent with the overall decrease in crashes. The 65+ age group saw a 32.1% decrease in persons involved, from 28 to 19, and the 45-54 age group experienced a 63.1% decrease, from 19 to 7. While top makes like Toyota, Ford, Honda, and Chevrolet all saw decreases in involvement, Hyundai vehicles involved in crashes increased from 2 to 7, a 250% rise.
Top Vehicle Makes (79 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Vehicle unit records
4 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (88 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 35 mph speed zones saw a substantial decrease, falling from 12 in April 2023 to 4 in April 2024, a 66.7% reduction. Crashes in 60 mph zones also decreased by 42.9%, from 7 to 4. Conversely, crashes in 20 mph zones increased by 50%, from 4 to 6.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · 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: 2024-04-01 through 2024-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-04-01 through 2024-04-30 (30 days)
- Geographic scope: PLYMOUTH, MA
- Total crash records analyzed: 51
- Total persons involved: 97
- Total vehicles involved: 79
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). "PLYMOUTH, MA Crash Intelligence Report: April 2024." Published June 21, 2026. Reporting period: 2024-04-01 to 2024-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/plymouth/april-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: 2024-04-01 – 2024-04-30
Generated: June 21, 2026 · All rights reserved