ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · PLYMPTON, MA · 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/plympton/2024-annual-report
Yearly Traffic Safety Analysis
51 CRASHES IN
PLYMPTON, MA
2024
In 2024, Plympton recorded 51 total vehicle crashes, a 31.1% decrease from the 74 crashes reported in 2023. The most notable change was the reduction in crash severity, with total injuries falling from 24 to 13 and fatalities dropping from one to zero.
51
▼ -31.1%was 74
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
13
▼ -45.8%was 24
Persons Injured
2
▼ -50.0%was 4
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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic crashes in Plympton showed a significant downward trend year-over-year. The total number of crashes decreased by 31.1%, from 74 in 2023 to 51 in 2024. This trend extended to crash outcomes, with total injuries declining by 45.8% and fatalities being eliminated entirely, down from one in the prior year.
2
Hit-and-Run Crashes — 2024
▼ -50.0% vs prior (4)
Hit-and-run incidents decreased in both count and as a percentage of total crashes. In 2024, there were two hit-and-run crashes, accounting for 3.9% of all incidents. This represents a reduction from 2023, which recorded four hit-and-run crashes at a rate of 5.4%.
Vulnerable Road User Casualties
0
Motorists Killed
13
Motorists Injured
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 significantly between the two periods. In 2024, Wednesday was the most frequent day for crashes with 13 incidents, a change from 2023 when Saturday saw the most crashes at 15. The peak hour for collisions also moved later in the day, from 5 PM in 2023 (12 crashes) to 7 PM in 2024 (5 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
Crash severity decreased in 2024 compared to the previous year, with fatal crashes dropping from one to zero. The total number of injuries reported fell from 24 to 13. While the count of serious injury crashes increased from one to three, minor injury crashes saw a substantial drop from 14 incidents in 2023 to five in 2024. Overall, non-injury crashes constituted a larger share of the total, rising from 66.2% in 2023 to 80.4% in 2024.
Outcome by Severity (Crash Events)
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
In both periods, 'No improper driving' was the most cited factor, though its count decreased from 29 crashes in 2023 to 24 in 2024. Several key driver-related factors saw significant reductions; crashes attributed to 'Failed to yield right of way' and 'Operating vehicle in erratic... manner' both fell from seven incidents to two. Conversely, crashes involving 'Failure to keep in proper lane or running off road' increased in count from three to five.
Officer-Reported Primary Contributing Cause
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
The conditions under which crashes occurred remained broadly similar, with most incidents in both years happening in clear weather and on dry roads. However, the share of crashes on wet road surfaces increased from 16.2% of all crashes in 2023 (12 incidents) to 25.5% in 2024 (13 incidents). Correspondingly, the proportion of crashes on dry roads fell from 73.0% to 66.7%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes remained consistent, with Ford, Chevrolet, and Toyota being the top three in both 2023 and 2024, though the counts for each decreased. Analysis of person demographics shows the 26-34 age group was the most represented in both years, with its count decreasing from 28 to 23. The most significant demographic shift was in the 35-44 age group, which saw its involvement decrease from 18 persons in 2023 to 8 in 2024.
Top Vehicle Makes (73 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
4 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (86 persons with recorded sex)
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
Crashes continued to occur most frequently in 40 mph and 35 mph speed zones in both periods, though the number of incidents in these zones decreased. In 2024, 21 crashes occurred in 40 mph zones and 14 in 35 mph zones, down from 33 and 20 respectively in 2023. The single fatal crash in 2023 occurred in a 30 mph zone; there were no fatalities in any speed zone in 2024.
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: PLYMPTON, MA
- Total crash records analyzed: 51
- Total persons involved: 89
- Total vehicles involved: 73
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). "PLYMPTON, 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/plympton/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved