ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · RUTLAND, 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/rutland/2023-annual-report
Yearly Traffic Safety Analysis
106 CRASHES IN
RUTLAND, MA
2023
In 2023, Rutland recorded 106 total crashes, a 2.9% increase from the 103 crashes reported in 2022. While overall crash volume and injury counts remained relatively stable, the data shows a notable shift in contributing factors, with crashes attributed to inattention more than doubling from 10 to 22 incidents year-over-year. Concurrently, crashes suspected to involve driving under the influence (DUI) fell from 9 in 2022 to 2 in 2023.
106
▲ 2.9%was 103
Total Crash Events
0
Persons Killed
30
▼ -3.2%was 31
Persons Injured
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. 2 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
Crash volume in Rutland saw a minor increase from 2022 to 2023, rising by 2.9% from 103 to 106 incidents. Despite the slight rise in total crashes, the number of people injured decreased marginally from 31 to 30. There were no traffic fatalities recorded in either period.
2
Hit-and-Run Crashes — 2023
1.9% hit-and-run rate this period vs 0.0% prior. Prior period: 0.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
2
Cyclists Injured
28
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 periods. The peak day for collisions moved from Sunday (23 crashes) in 2022 to Saturday (18 crashes) in 2023. The single busiest hour also shifted, from 2 p.m. in the prior year (12 crashes) to a tie between 2 p.m. and 5 p.m. in the current year, each with 10 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
No fatal crashes were recorded in either 2022 or 2023. The distribution of injury severity changed, with crashes resulting in serious injuries decreasing from 4 in 2022 to 2 in 2023. Conversely, the count of crashes involving minor injuries increased from 15 to 19 over the same period, while those with possible injuries fell from 7 to 4.
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
While 'No improper driving' was the most common factor in both periods, its count was nearly identical with 37 crashes in 2023 versus 38 in 2022. The most significant change was in crashes attributed to 'Inattention', which saw a 120% increase in count from 10 incidents in 2022 to 22 in 2023, becoming the second-leading factor. 'Failed to yield right of way' also increased from 6 to 11 crashes, while 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner', the second-most cited factor in 2022 with 11 crashes, was not a top-listed factor 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
Crashes in clear weather and daylight remained the majority in both years with little change. However, collisions in cloudy conditions doubled from 7 in 2022 to 14 in 2023. There was a notable decrease in crashes on adverse road surfaces, with incidents on snowy or icy roads falling from a combined 19 in 2022 to 12 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 vehicle makes most frequently involved in crashes shifted year-over-year. In 2023, Toyota became the most common make with 27 vehicles involved, a significant increase from 15 in 2022. Ford, the top make in 2022 with 27 vehicles, saw its involvement decrease to 22. The age demographics of persons involved in crashes also changed, with a notable increase in the 45-54 age group (from 18 to 33 people) and the 26-34 age group (from 24 to 35 people).
Top Vehicle Makes (168 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
2 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (192 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 showed a shift toward higher-speed areas in 2023. The number of crashes in 50 mph zones increased from 26 in 2022 to 33 in 2023, and incidents in 45 mph zones rose from 13 to 17. In contrast, crashes in 40 mph zones decreased from 24 to 20. 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: RUTLAND, MA
- Total crash records analyzed: 106
- Total persons involved: 200
- Total vehicles involved: 168
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). "RUTLAND, 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/rutland/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