ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GREAT BARRINGTON, MA · FEBRUARY 2022
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.
Monthly Traffic Safety Analysis
12 CRASHES IN
GREAT BARRINGTON, MA
FEBRUARY 2022
Total crashes in GREAT BARRINGTON remained stable year-over-year, with 12 crashes recorded in February 2022 and 12 in February 2021. The most notable shifts include the emergence of speeding-related crashes, which increased from 0 in February 2021 to 2 in February 2022, and hit-and-run crashes, which increased from 0 to 1 in the same period. Additionally, total injuries decreased by 33.3%, from 3 in February 2021 to 2 in February 2022.
12
Total Crash Events
0
Persons Killed
2
▼ -33.3%was 3
Persons Injured
1
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend for total crashes in GREAT BARRINGTON remained stable, with 12 crashes reported in both February 2022 and February 2021, representing a 0% change. However, total injuries decreased by 33.3%, from 3 in February 2021 to 2 in February 2022. Fatalities remained at 0 in both periods.
1
Hit-and-Run Crashes — February 2022
8.3% hit-and-run rate this period vs 0.0% prior. Prior period: 0.
Vulnerable Road User Casualties
0
Motorists Killed
2
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes shifted year-over-year. In February 2022, the peak days for crashes were Sunday and Saturday, each with 3 crashes, while in February 2021, Monday was the peak day with 4 crashes. The peak hour for crashes in February 2022 was 9p with 2 crashes, contrasting with February 2021 where 3p and 5p each had 2 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatalities reported in either February 2022 or February 2021. Total injuries decreased from 3 in February 2021 to 2 in February 2022, representing a 33.3% reduction. Specifically, February 2021 included 1 serious injury crash and 1 possible injury crash, whereas February 2022 reported 2 possible injury crashes and no serious injury crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Most severe injury per crash record
Top Contributing Factors
The contributing factor 'No improper driving' significantly increased from 1 crash in February 2021 to 6 crashes in February 2022. 'Driving too fast for conditions' and 'Over-correcting/over-steering' each accounted for 1 crash in February 2022, neither of which was reported in February 2021. Conversely, several factors present in February 2021, such as 'Failed to yield right of way,' 'Failure to keep in proper lane or running off road,' 'Inattention,' 'Distracted,' 'Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway,' and 'Made an improper turn' (each contributing to 1 crash), were not reported in February 2022.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 5 in February 2021 to 8 in February 2022, while crashes in cloudy conditions decreased from 2 to 1. Crashes on dry road surfaces remained stable at 8 in both periods, but crashes on icy roads increased from 0 to 1. For lighting conditions, crashes during daylight increased from 7 to 8, and those in 'Dark - roadway not lighted' conditions increased from 1 to 3.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Road surface condition field
Vehicles & Demographics
Top Vehicle Makes (20 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Vehicle unit records
1 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (21 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 25 mph speed limit zone appeared in February 2022, accounting for 4 crashes, whereas no crashes were reported in this zone in February 2021. Crashes in the 30 mph zone increased from 1 in February 2021 to 2 in February 2022, and crashes in the 45 mph zone also increased from 1 to 2. No fatalities were reported in any speed limit zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · 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: 2022-02-01 through 2022-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-02-01 through 2022-02-28 (28 days)
- Geographic scope: GREAT BARRINGTON, MA
- Total crash records analyzed: 12
- Total persons involved: 22
- Total vehicles involved: 20
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). "GREAT BARRINGTON, MA Crash Intelligence Report: February 2022." Published June 21, 2026. Reporting period: 2022-02-01 to 2022-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/great-barrington/february-2022-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: 2022-02-01 – 2022-02-28
Generated: June 21, 2026 · All rights reserved