Monthly Traffic Safety Analysis

15 CRASHES IN
RUTLAND, MA
DECEMBER 2024

All metrics benchmarked againstDecember 2023

In December 2024, Rutland experienced 15 crashes, an increase from 7 crashes reported in December 2023. This represents a substantial 114.3% year-over-year rise in total crashes. The most notable shift was the increase in total injuries, which climbed from 1 in the prior period to 9 in the current period.

15

114.3%was 7

Total Crash Events

0

Persons Killed

9

800.0%was 1

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 · 2024-12-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends in Rutland show a significant increase year-over-year, with total crashes rising from 7 in December 2023 to 15 in December 2024. This marks a 114.3% increase in crash incidents. Total injuries also saw a substantial rise, from 1 in the prior period to 9 in the current period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 0%

6

Motorists Injured

Prior: 1500.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · 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. While Saturday remained a peak day for crashes, increasing from 2 to 4 incidents, the peak hour shifted from 2 PM (with 2 crashes) in December 2023 to 9 AM (with 4 crashes) in December 2024. Mondays also saw a notable increase in crashes, rising from 1 in the prior year to 4 in the current year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero in both December 2023 and December 2024. However, injury severity increased in the current period, with 1 serious injury crash (6.7% of total crashes) reported in December 2024, compared to none in December 2023. Minor injury crashes also increased in count from 1 to 4, representing a rise from 14.3% to 26.7% of all crashes year-over-year.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes6.7%
Minor Injury4minor injury crashes26.7%
300.0%prior 1
No Injury10no injury crashes66.7%
66.7%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'No improper driving', increased in count from 3 crashes in December 2023 to 5 crashes in December 2024. Factors such as 'Failed to yield right of way' and 'Driving too fast for conditions' emerged in December 2024 with 3 and 2 crashes respectively, having no recorded incidents in the prior year. Conversely, 'Distracted' driving, which accounted for 1 crash in December 2023, was not listed as a factor in December 2024, though 'Inattention' appeared with 1 crash.

Officer-Reported Primary Contributing Cause

No improper driving5 (33.3%)
Failed to yield right of way3 (20%)
Other improper action2 (13.3%)
Driving too fast for conditions2 (13.3%)
Failure to keep in proper lane or running off road1 (6.7%)
Disregarded traffic signs, signals, road markings1 (6.7%)
Inattention1 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in adverse weather conditions (non-clear) increased from 2 incidents (28.6% of total crashes) in December 2023 to 7 incidents (46.7% of total crashes) in December 2024. Similarly, crashes on non-dry road surfaces rose from 1 (14.3% of total crashes) to 8 (53.3% of total crashes) year-over-year. Crashes occurring in non-daylight conditions showed a slight proportional decrease, from 3 incidents (42.9% of total crashes) to 6 incidents (40% of total crashes).

Weather

Clear8 (53.3%)
60.0%prior 5
Cloudy3 (20.0%)
Cloudy/Snow1 (6.7%)
Rain/Fog, smog, smoke1 (6.7%)
Rain/Other1 (6.7%)
Snow1 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight9 (60.0%)
Dark - lighted roadway4 (26.7%)
Dark - roadway not lighted1 (6.7%)
Dawn1 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry7 (46.7%)
16.7%prior 6
Wet4 (26.7%)
Slush2 (13.3%)
Snow2 (13.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (24 vehicles)

1
HONDA4 (16.7%)
2
FORD4 (16.7%)
3
NISSAN2 (8.3%)
4
DODGE2 (8.3%)
5
CHEVROLET2 (8.3%)
6
TOYOTA2 (8.3%)
7
HYUNDAI2 (8.3%)
8
VOLKSWAGEN1 (4.2%)
9
INTL1 (4.2%)
10
KIA1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Vehicle unit records

Sex Distribution (32 persons with recorded sex)

Male19 (59.4%)
216.7%prior 6
Female13 (40.6%)
333.3%prior 3

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · Person-level records linked to crash events

Speed Limit Zones

No fatal crashes were recorded in any speed limit zone during either period. The distribution of crashes across speed limits showed increases in several zones, with crashes at 30 mph rising from 1 to 4, at 40 mph from 1 to 3, and at 50 mph from 2 to 5. A crash occurred in a 20 mph zone in December 2023, but no crashes were reported at that speed limit in December 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-12-01 to 2024-12-31 · 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: 2024-12-01 through 2024-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-12-01 through 2024-12-31 (31 days)
  • Geographic scope: RUTLAND, MA
  • Total crash records analyzed: 15
  • Total persons involved: 32
  • Total vehicles involved: 24

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: December 2024." Published June 21, 2026. Reporting period: 2024-12-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/rutland/december-2024-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 — December 2024 | ThatCarHitMe.com