ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · PLYMPTON, MA · 2023
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/2023-annual-report
Yearly Traffic Safety Analysis
74 CRASHES IN
PLYMPTON, MA
2023
In 2023, Plympton recorded 74 total vehicle crashes, an increase of 12.1% from the 66 crashes recorded in 2022. While the total number of people injured decreased slightly from 26 to 24, the most significant change was the occurrence of one fatal crash in 2023, whereas there were no fatal crashes in the prior year.
74
▲ 12.1%was 66
Total Crash Events
1
Persons Killed
24
▼ -7.7%was 26
Persons Injured
4
▲ 100.0%was 2
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. 5 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, traffic crashes in Plympton increased by 12.1% from 2022 to 2023, rising from 66 to 74 incidents. This increase was accompanied by the city's first fatal crash in this two-year period. However, the total number of persons injured in crashes saw a slight decrease, falling from 26 in 2022 to 24 in 2023.
4
Hit-and-Run Crashes — 2023
▲ 100.0% vs prior (2)
Hit-and-run incidents increased in both count and rate from 2022 to 2023. The number of hit-and-run crashes doubled from 2 to 4. This corresponds to an increase in the hit-and-run rate from 3.0 per 100 crashes in 2022 to 5.4 per 100 crashes in 2023.
Vulnerable Road User Casualties
1
Motorists Killed
24
Motorists Injured
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 shifted between the two years. In 2023, the peak day for crashes was Saturday with 15 incidents, a change from 2022 when Friday was the peak day with 14 crashes. The most common time for a crash also changed, moving from a tie between 6 AM and 6 PM (7 crashes each) in 2022 to a more pronounced peak at 5 PM (12 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 saw a notable change with the appearance of one fatal incident in 2023, resulting in a fatal crash rate of 1.4%, up from zero in 2022. Despite the overall increase in total crashes, the proportion of crashes resulting in any injury decreased from 33.3% (22 crashes) in 2022 to 25.7% (19 crashes) in 2023. The share of no-injury crashes remained stable, accounting for 65.2% of crashes in 2022 and 66.2% in 2023.
Outcome by Severity (Crash Events)
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 factor in both periods was 'No improper driving,' with its count increasing from 21 in 2022 to 29 in 2023. Significant shifts occurred in other top factors; crashes attributed to 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' increased from a count of 2 to 7, and 'Failed to yield right of way' increased from a count of 3 to 7. Conversely, crashes involving 'Distracted' as a factor decreased from a count of 5 in 2022 to just 1 in 2023.
Officer-Reported Primary Contributing Cause
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
The proportion of crashes occurring on dry road surfaces remained nearly unchanged, accounting for 73% of incidents in 2023 compared to 72.7% in 2022. There was a shift in lighting conditions, with a smaller percentage of crashes happening in the dark (31.1% in 2023 vs. 45.5% in 2022) and a corresponding increase in daylight crashes (58.1% in 2023 vs. 50% in 2022). The share of crashes in clear weather decreased slightly from 72.7% in 2022 to 67.6% in 2023.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
The ranking of top vehicle makes involved in crashes shifted year-over-year. In 2023, Ford was the most frequent make with 14 vehicles, followed by Toyota with 11; this reverses the 2022 ranking where Toyota led with 19 vehicles followed by Ford with 15. Analysis of persons involved shows a demographic shift, with the 26-34 age group becoming the largest cohort in 2023 (28 persons), up from 15 persons in 2022 when the 21-25 age group was the largest (16 persons).
Top Vehicle Makes (95 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
7 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (99 persons with recorded sex)
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 remained largely consistent between the two years, with 40 mph zones accounting for the highest number of incidents in both 2023 (33 crashes) and 2022 (33 crashes). Crashes in 35 mph zones increased from 16 to 20. The single fatal crash recorded in 2023 occurred in a 30 mph zone, which had no fatal crashes in the prior year.
Fatal crashes by zone: 30 mph: 1 of 8 (12.5%)
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: PLYMPTON, MA
- Total crash records analyzed: 74
- Total persons involved: 106
- Total vehicles involved: 95
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: 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/plympton/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved