Monthly Traffic Safety Analysis

3 CRASHES IN
RUTLAND, MA
FEBRUARY 2023

All metrics benchmarked againstFebruary 2022

Total crashes in Rutland decreased significantly from 13 in February 2022 to 3 in February 2023, representing a 76.9% reduction. The most notable year-over-year shift is this substantial decline in overall crash incidents.

3

-76.9%was 13

Total Crash Events

0

Persons Killed

1

-66.7%was 3

Persons Injured

0

Fatal Crash Events

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend for February in Rutland shows a significant decrease in crash incidents. Total crashes fell by 10, from 13 in February 2022 to 3 in February 2023. This represents a substantial decline in crash frequency year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

1

Motorists Injured

Prior: 3-66.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Friday in both periods, though the count decreased from 4 crashes in February 2022 to 1 crash in February 2023. The peak crash hour shifted from 3 PM with 3 crashes in February 2022 to 9 PM with 1 crash in February 2023. This indicates a shift in the timing of peak crash activity.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both February 2022 and February 2023. Total injuries decreased from 3 in February 2022 to 1 in February 2023. In February 2023, 33.3% of crashes involved minor injuries, compared to 7.7% in February 2022, while crashes with no injuries decreased from 76.9% to 66.7% of the total.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes33.3%
0.0%prior 1
No Injury2no injury crashes66.7%
-80.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Most severe injury per crash record

Road & Environmental Conditions

In February 2023, 2 of 3 crashes occurred on icy road surfaces, compared to 1 of 13 crashes on ice in February 2022. Daylight was a factor in 1 of 3 crashes in February 2023, a decrease from 7 of 13 crashes in daylight in February 2022. Weather conditions in February 2023 were varied, with one crash each reported in cloudy, severe crosswinds, and sleet/snow conditions, contrasting with February 2022 where clear conditions were dominant in 6 of 13 crashes.

Weather

Cloudy1 (33.3%)
Severe crosswinds1 (33.3%)
Sleet, hail (freezing rain or drizzle)/Snow1 (33.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Weather condition at time of crash

Lighting

Dark - roadway not lighted1 (33.3%)
Daylight1 (33.3%)
-85.7%prior 7
Dusk1 (33.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Lighting condition field

Road Surface

Ice2 (66.7%)
Dry1 (33.3%)
-85.7%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (3 vehicles)

1
HONDA1 (33.3%)
2
HYUNDAI1 (33.3%)
3
KIA1 (33.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Vehicle unit records

Sex Distribution (4 persons with recorded sex)

Female3 (75.0%)
-25.0%prior 4
Male1 (25.0%)
-91.7%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Person-level records linked to crash events

Speed Limit Zones

In February 2023, crashes were distributed across 25, 35, and 50 mph speed zones, with one crash in each. In contrast, February 2022 saw crashes across a wider range of speed limits, with the highest number of crashes (5) occurring in 50 mph zones. Fatal crashes remained at 0 in all reported speed zones for both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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: 2023-02-01 through 2023-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-02-01 through 2023-02-28 (28 days)
  • Geographic scope: RUTLAND, MA
  • Total crash records analyzed: 3
  • Total persons involved: 4
  • Total vehicles involved: 3

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: February 2023." Published June 21, 2026. Reporting period: 2023-02-01 to 2023-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/rutland/february-2023-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

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Rutland, MA Crash Report — February 2023 | ThatCarHitMe.com