ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · PLYMOUTH, 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/plymouth/2023-annual-report
Yearly Traffic Safety Analysis
881 CRASHES IN
PLYMOUTH, MA
2023
In 2023, Plymouth recorded 881 total traffic crashes, a slight decrease from the 891 crashes documented in 2022, representing a 1.1% year-over-year reduction. While the overall crash volume remained relatively stable, the number of people injured fell by 12.5% from 368 to 322. The most notable shift was a 63.6% increase in crashes involving speeding, which rose from 33 incidents in 2022 to 54 in 2023.
881
▼ -1.1%was 891
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
322
▼ -12.5%was 368
Persons Injured
25
▼ -7.4%was 27
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. 13 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
The overall trend in Plymouth shows a slight decline in traffic collisions from 2022 to 2023. Total crashes decreased by 1.1%, from 891 to 881. More significantly, the outcomes of these crashes became less severe, with total injuries dropping 12.5% from 368 to 322 and total fatalities decreasing from two to one.
25
Hit-and-Run Crashes — 2023
▼ -7.4% vs prior (27)
Hit-and-run crashes saw a slight decline between the two periods. The total count of hit-and-run incidents decreased from 27 in 2022 to 25 in 2023. The hit-and-run rate, as a percentage of all crashes, also trended down slightly, from 3.0% in 2022 to 2.8% in 2023.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
4
Pedestrians Injured
7
Cyclists Injured
310
Motorists Injured
1
Other 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 timing of crashes shifted between the two periods. In 2022, the peak day for crashes was Friday with 165 incidents, whereas in 2023, the peak shifted to midweek, with Wednesday and Thursday each recording 135 crashes. The peak hour for collisions also moved slightly earlier, from 3 p.m. in 2022 (76 crashes) to 4 p.m. in 2023 (72 crashes).
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 decreased from 2022 to 2023. The number of fatal crashes was halved, from two in 2022 to one in 2023, and the fatal crash rate fell from 0.22% to 0.11%. The proportion of crashes resulting in any injury also declined, from 31.4% of all crashes in 2022 to 26.3% in 2023. Correspondingly, property-damage-only crashes increased their share from 67.1% to 72.1% of all incidents.
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
In 2023, 'Inattention' was the leading contributing factor, cited in 169 crashes, up from 131 crashes in 2022 when it was the second-ranked factor. This represents a 29% increase in count for inattention-related crashes. Conversely, crashes with 'No improper driving' cited decreased by 26.2%, from 145 in 2022 to 107 in 2023. Crashes attributed to 'Driving too fast for conditions' increased by 65.2% in count, from 23 to 38 incidents year-over-year.
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 majority of crashes in both years occurred during daylight on dry roads. In 2023, 67.0% of crashes happened in daylight, compared to 62.9% in 2022. There was a slight increase in the proportion of crashes on wet road surfaces, which accounted for 19.3% of incidents in 2023, up from 15.8% in 2022. Crashes in clear weather conditions remained dominant but saw their share decrease slightly from 72.5% in 2022 to 70.9% 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 top vehicle makes involved in crashes remained consistent, with Toyota, Ford, and Honda being the most frequent in both 2022 and 2023. However, the age demographics of persons involved in crashes showed a notable shift. The 65+ age group became the largest single cohort in 2023, with 302 individuals involved, an increase from 265 in 2022. The 0-15 age group also saw a significant increase in involvement, from 113 persons in 2022 to 169 in 2023.
Top Vehicle Makes (1,573 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
108 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,878 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
In both periods, the highest number of crashes occurred in 30 mph zones, with counts increasing from 280 in 2022 to 302 in 2023. Crashes in 35 mph zones decreased from 141 to 117, while incidents in 40 mph zones rose from 128 to 132. The location of fatal crashes also shifted; the two fatalities in 2022 occurred in a 40 mph zone, while the single fatality in 2023 happened in a 35 mph zone.
Fatal crashes by zone: 35 mph: 1 of 117 (0.855%)
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: PLYMOUTH, MA
- Total crash records analyzed: 881
- Total persons involved: 2,023
- Total vehicles involved: 1,573
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: 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/plymouth/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