Yearly Traffic Safety Analysis

3 CRASHES IN
SANDISFIELD, MA
2023

All metrics benchmarked against2022

In 2023, Sandisfield recorded 3 traffic crashes, a 66.7% decrease from the 9 crashes reported in 2022. While total crashes fell significantly, the number of injuries remained unchanged at one person injured in each period. The most notable shift was this sharp decline in overall crash volume, alongside a change in the timing of crashes from daytime in 2022 to evening hours in 2023.

3

-66.7%was 9

Total Crash Events

0

Persons Killed

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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in traffic crashes in Sandisfield shows a significant year-over-year decrease. Total crashes fell by 66.7%, from 9 incidents in 2022 to 3 in 2023. The number of injuries held steady at 1, and no fatalities occurred in either period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

1

Motorists Injured

Prior: 10.0%

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 significantly between the two periods. In 2023, the peak day for crashes was Saturday with 2 incidents, a change from Monday which saw 3 crashes in the prior year. Similarly, the peak hour moved from the afternoon at 1 p.m. in 2022 to the evening hours in 2023, with crashes occurring at 6 p.m., 7 p.m., and 9 p.m.

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

There were no fatal crashes recorded in either 2023 or 2022. The number of injury-involved crashes remained constant at one crash per year. However, the proportion of crashes involving an injury increased from 11.1% of all crashes in 2022 to 33.3% in 2023 due to the overall reduction in total crashes.

Outcome by Severity (Crash Events)

Possible Injury1possible injury crashes33.3%
No Injury2no injury crashes66.7%
-71.4%prior 7

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 reported factor in 2023 was 'No improper driving', cited in 2 of the 3 crashes, a count decrease from 3 citations in 2022. 'Failure to keep in proper lane or running off road' was cited in one crash in both years. Factors such as 'Inattention' and 'Made an improper turn', each cited once in 2022, were not reported as contributing factors in 2023.

Officer-Reported Primary Contributing Cause

No improper driving2 (66.7%)
Failure to keep in proper lane or running off road1 (33.3%)

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

In 2023, all 3 crashes occurred in clear or partly cloudy weather, whereas in 2022, one of the 9 crashes (11.1%) occurred in snow. Regarding road surface, the proportion of crashes on non-dry roads decreased from 44.4% (4 of 9 crashes) in 2022 to 33.3% (1 of 3 crashes) in 2023. Lighting condition data was not available for 2023, preventing a direct year-over-year comparison.

Weather

Clear2 (66.7%)
-71.4%prior 7
Clear/Cloudy1 (33.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Road Surface

Dry2 (66.7%)
-60.0%prior 5
Wet1 (33.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (3 vehicles)

1
FORD1 (33.3%)
2
GMC1 (33.3%)
3
SUBARU1 (33.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

Sex Distribution (3 persons with recorded sex)

Female2 (66.7%)
-50.0%prior 4
Male1 (33.3%)
-90.0%prior 10

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 across speed zones shifted between the two years. In 2022, the most crashes (4) occurred in the 45 mph zone. In 2023, the 3 recorded crashes were spread across 35, 40, and 55 mph zones, with one crash occurring in a 55 mph zone which had no crashes in the prior year. No fatal crashes were reported in any speed zone for 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: SANDISFIELD, MA
  • Total crash records analyzed: 3
  • Total persons involved: 3
  • 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). "SANDISFIELD, 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/sandisfield/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

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Sandisfield, MA Crash Report — 2023 | ThatCarHitMe.com