ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CLINTON, 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/clinton/2023-annual-report
Yearly Traffic Safety Analysis
106 CRASHES IN
CLINTON, MA
2023
In 2023, Clinton recorded 106 total vehicle crashes, a 17.8% increase from the 90 crashes documented in 2022. While there were no fatalities in either year, the number of reported injuries rose by 46.7%, from 30 in 2022 to 44 in 2023. The most notable year-over-year change was the increase in crashes attributed to "Failed to yield right of way," which more than doubled in count from 13 to 27.
106
▲ 17.8%was 90
Total Crash Events
0
Persons Killed
44
▲ 46.7%was 30
Persons Injured
3
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. 8 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, crash trends in Clinton show an increase year-over-year. Total crashes rose by 17.8% from 90 in 2022 to 106 in 2023. This was accompanied by a more substantial 46.7% increase in the number of people injured, which grew from 30 to 44. Fatalities remained stable at zero for both periods.
3
Hit-and-Run Crashes — 2023
2.8% hit-and-run rate this period vs 0.0% prior. Prior period: 0.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
2
Pedestrians Injured
42
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 Tuesday with 20 incidents, a change from 2022 when Friday was the peak day with 20 crashes. Similarly, the peak hour for crashes moved earlier in the day, from the 5 p.m. hour (15 crashes) in 2022 to the 3 p.m. hour (14 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
No fatal crashes were recorded in either 2022 or 2023. However, the severity distribution of non-fatal crashes shifted; the share of crashes involving minor injuries more than doubled, from 6.7% of crashes in 2022 to 14.2% in 2023. Conversely, the proportion of crashes resulting in serious injuries decreased from 2.2% to 0.9%, and possible injury crashes fell from 20.0% to 13.2% of the total.
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 factors for crashes changed significantly year-over-year. In 2023, "Failed to yield right of way" became the top factor, cited in 27 crashes (25.5% share), more than doubling from its 2022 count of 13. This displaced 2022's top factor, "No improper driving," which saw its count decrease from 19 to 17. Meanwhile, crashes attributed to "Followed too closely" saw a notable drop, with the count falling by 45.5% from 11 incidents in 2022 to 6 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
While the majority of crashes in both periods occurred in daylight on dry roads, there were shifts in specific conditions. The number of crashes happening in "Dark - lighted roadway" conditions increased from 20 in 2022 to 32 in 2023, raising its share of total crashes from 22.2% to 30.2%. Additionally, crashes under "Cloudy/Cloudy" weather conditions more than doubled, from 8 in 2022 to 18 in 2023. The proportion of crashes on dry road surfaces remained relatively stable, accounting for 81.1% of crashes in 2023 compared to 83.3% in 2022.
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 makes of vehicles involved in crashes showed a notable shift, with Toyota's count increasing from 10 in 2022 to 36 in 2023, making it the most common make by a large margin. The age demographics of all persons involved in crashes also changed, with significant increases in the 21-25 age group (from 13 to 32 persons) and the 65+ age group (from 17 to 36 persons). Conversely, the number of persons in the 55-64 age group decreased from 40 to 29.
Top Vehicle Makes (204 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
23 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (246 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 2022 and 2023, the overwhelming majority of crashes occurred in 30 mph speed zones. The number of crashes in these zones increased from 83 to 103, reflecting the overall year-over-year rise in total incidents. There were no significant shifts of crashes into higher or lower speed zones, and no fatal crashes were recorded in any speed zone during either period.
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: CLINTON, MA
- Total crash records analyzed: 106
- Total persons involved: 266
- Total vehicles involved: 204
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). "CLINTON, 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/clinton/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