Yearly Traffic Safety Analysis

9 CRASHES IN
SANDISFIELD, MA
2022

All metrics benchmarked against2021

In 2022, Sandisfield recorded 9 total crashes, an increase of 28.6% from the 7 crashes reported in 2021. Despite the rise in total incidents, the most notable year-over-year shift was a significant decrease in crash severity. The number of fatalities fell from one in 2021 to zero in 2022, and total injuries decreased from six to one.

9

28.6%was 7

Total Crash Events

0

-100.0%was 1

Persons Killed

1

-83.3%was 6

Persons Injured

0

-100.0%was 1

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in Sandisfield shows an increase in total crashes, rising from 7 incidents in 2021 to 9 in 2022. However, the severity of these crashes decreased substantially, as fatalities were eliminated and the number of people injured dropped from 6 in the prior year to 1 in the current year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1-100.0%

1

Motorists Injured

Prior: 6-83.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Crash timing shifted from weekends to weekdays year-over-year. In 2022, the peak day for crashes was Monday with 3 incidents, a change from 2021 when crashes peaked on Saturday and Sunday with 2 crashes each. The peak hour also became more concentrated in 2022, with 3 crashes occurring at 1 p.m., whereas 2021 saw a more even distribution across several afternoon and evening hours.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity significantly decreased in 2022 compared to the previous year. The fatal crash rate dropped from 14.3% (1 crash) in 2021 to 0% in 2022. The proportion of crashes resulting in any injury also fell, with only one minor injury crash (11.1% of total) in 2022, down from five injury-involved crashes in 2021. Consequently, no-injury crashes became the dominant type, accounting for 77.8% of all incidents in 2022, up from 28.6% in 2021.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes11.1%
-66.7%prior 3
No Injury7no injury crashes77.8%
250.0%prior 2

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes shifted between periods. In 2022, 'No improper driving' was the most common circumstance, cited in 3 crashes, whereas in 2021, the top factor was 'Fatigued/asleep' with 2 crashes. The count for crashes attributed to being fatigued or asleep dropped to zero in 2022. The number of crashes involving 'Inattention' and 'Failure to keep in proper lane or running off road' each held steady at one incident in both years.

Officer-Reported Primary Contributing Cause

No improper driving3 (33.3%)
Failure to keep in proper lane or running off road1 (11.1%)
Inattention1 (11.1%)
Made an improper turn1 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Weather

Clear7 (77.8%)
Cloudy1 (11.1%)
Snow1 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight7 (77.8%)
Dark - roadway not lighted2 (22.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry5 (55.6%)
Wet2 (22.2%)
Sand, mud, dirt, oil, gravel1 (11.1%)
Snow1 (11.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (11 vehicles)

1
TOYOTA2 (18.2%)
2
DODGE2 (18.2%)
3
FORD2 (18.2%)
4
CHEVROLET2 (18.2%)
5
SUBARU1 (9.1%)
6
VOLVO1 (9.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

1 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (14 persons with recorded sex)

Male10 (71.4%)
-16.7%prior 12
Female4 (28.6%)
300.0%prior 1

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events

Speed Limit Zones

In both 2021 and 2022, the 45 mph speed zone was the site of the most crashes, with 4 incidents recorded each year. The single fatal crash in 2021 occurred within this 45 mph zone, while no fatal crashes were reported in any zone in 2022. The distribution of crashes in other zones shifted; incidents in 25 mph and 55 mph zones that occurred in 2021 were not present in 2022, while crashes in 30, 35, and 40 mph zones appeared in the 2022 data.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: SANDISFIELD, MA
  • Total crash records analyzed: 9
  • Total persons involved: 15
  • Total vehicles involved: 11

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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/sandisfield/2022-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

Sandisfield, MA Crash Report — 2022 | ThatCarHitMe.com