Monthly Traffic Safety Analysis

23 CRASHES IN
GRANBY, MA
JUNE 2022

All metrics benchmarked againstJune 2021

In June 2022, GRANBY experienced 23 crashes, a notable increase from the 13 crashes reported in June 2021, representing a 76.9% rise. This period also saw a significant increase in crashes attributed to Inattention, rising from 3 to 11 incidents.

23

76.9%was 13

Total Crash Events

0

Persons Killed

10

100.0%was 5

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in GRANBY saw a substantial increase year-over-year. Total crashes rose from 13 in June 2021 to 23 in June 2022, marking a 76.9% increase in reported incidents.

1

Hit-and-Run Crashes — June 2022

4.3% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

9

Motorists Injured

Prior: 580.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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 year-over-year, with the peak day moving from Tuesday in June 2021 (3 crashes) to Saturday in June 2022 (6 crashes). The peak hour also changed, from 3 PM with 3 crashes in the prior period to 2 PM with 5 crashes in the current period. Notably, crashes in the evening hours, such as 7 PM and 9 PM, saw increases from 0 to 3 and 0 to 4 crashes respectively.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Both periods reported zero fatalities and zero fatal crashes. Total injuries increased from 5 in June 2021 to 10 in June 2022. While the prior period had 4 minor injuries (30.8% of crashes), the current period saw 5 minor injuries (21.7% of crashes) and 4 possible injuries (17.4% of crashes).

Outcome by Severity (Crash Events)

Minor Injury5minor injury crashes21.7%
25.0%prior 4
Possible Injury4possible injury crashes17.4%
No Injury14no injury crashes60.9%
75.0%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Most severe injury per crash record

Top Contributing Factors

The most significant shift in contributing factors was seen in 'Inattention,' which increased from 3 crashes in June 2021 to 11 crashes in June 2022. Crashes where 'No improper driving' was cited also rose, from 1 incident to 5 incidents year-over-year. 'Failure to keep in proper lane or running off road' and 'Failed to yield right of way' remained consistent with 2 and 1 crash respectively across both periods.

Officer-Reported Primary Contributing Cause

Inattention11 (47.8%)
No improper driving5 (21.7%)
Failure to keep in proper lane or running off road2 (8.7%)
Followed too closely1 (4.3%)
Failed to yield right of way1 (4.3%)
Over-correcting/over-steering1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather increased from 10 in June 2021 to 17 in June 2022, while rain-related crashes doubled from 1 to 2 incidents. Similarly, crashes on dry road surfaces increased from 10 to 20 year-over-year, and wet surface crashes rose from 2 to 3. The data for lighting conditions in the prior period is not available for comparison.

Weather

Clear17 (73.9%)
70.0%prior 10
Cloudy4 (17.4%)
Rain2 (8.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Weather condition at time of crash

Lighting

Daylight16 (69.6%)
Dark - lighted roadway3 (13.0%)
Dawn2 (8.7%)
Dark - roadway not lighted1 (4.3%)
Dark - unknown roadway lighting1 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Lighting condition field

Road Surface

Dry20 (87.0%)
100.0%prior 10
Wet3 (13.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (36 vehicles)

1
FORD6 (16.7%)
2
HONDA6 (16.7%)
3
NISSAN4 (11.1%)
4
HYUNDAI3 (8.3%)
5
TOYOTA2 (5.6%)
6
CHEVROLET2 (5.6%)
7
DODGE2 (5.6%)
8
SUBARU1 (2.8%)
9
VOLVO1 (2.8%)
10
ACURA1 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Vehicle unit records

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

Sex Distribution (45 persons with recorded sex)

Male26 (57.8%)
73.3%prior 15
Female19 (42.2%)
90.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 35 mph zones saw a notable increase, rising from 1 in June 2021 to 7 in June 2022. Crashes in 40 mph zones also increased from 5 to 7, and 45 mph zones from 2 to 4. Conversely, 25 mph zones, which had 2 crashes in the prior period, reported no crashes in the current period. No fatalities were reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-06-01 to 2022-06-30 · 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: 2022-06-01 through 2022-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-06-01 through 2022-06-30 (30 days)
  • Geographic scope: GRANBY, MA
  • Total crash records analyzed: 23
  • Total persons involved: 49
  • Total vehicles involved: 36

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). "GRANBY, MA Crash Intelligence Report: June 2022." Published June 21, 2026. Reporting period: 2022-06-01 to 2022-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/granby/june-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

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Granby, MA Crash Report — June 2022 | ThatCarHitMe.com