Monthly Traffic Safety Analysis

11 CRASHES IN
GRANBY, MA
MARCH 2023

All metrics benchmarked againstMarch 2022

GRANBY experienced a stable total number of crashes with 11 incidents in March 2023, identical to March 2022. Despite the consistent crash count, there was a significant 60% reduction in total injuries, decreasing from 5 in March 2022 to 2 in March 2023. Additionally, DUI-related crashes were completely eliminated in March 2023, down from 2 incidents in the prior year.

11

Total Crash Events

0

Persons Killed

2

-60.0%was 5

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 · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in GRANBY for total crashes remained stable year-over-year, with 11 crashes reported in both March 2023 and March 2022. However, there was a positive trend in injury reduction, with total injuries decreasing by 60% from 5 to 2, and no fatalities reported in either period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 5-60.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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, with the peak day for crashes moving from Thursday in March 2022 (3 crashes) to Friday in March 2023 (3 crashes). The peak hour also changed, with March 2022 seeing a peak at 1 PM (2 crashes) while March 2023 experienced peaks at 7 AM, 10 AM, and 5 PM, each with 2 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution of crashes improved significantly year-over-year, with no serious injuries (A) reported in March 2023 compared to 2 serious injuries in March 2022. Overall injuries decreased by 60%, from 5 in March 2022 (2 serious, 2 minor, 1 possible) to 2 in March 2023 (1 minor, 1 possible).

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes9.1%
-50.0%prior 2
Possible Injury1possible injury crashes9.1%
No Injury9no injury crashes81.8%
28.6%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors shifted considerably, with 'Inattention' becoming the most frequent factor in March 2023, accounting for 6 crashes, a factor not prominently listed in the prior period. 'No improper driving' decreased from 3 crashes in March 2022 to 2 crashes in March 2023. Factors such as 'Fatigued/asleep' and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner', each contributing to 1 crash in March 2022, were not reported in March 2023.

Officer-Reported Primary Contributing Cause

Inattention6 (54.5%)
No improper driving2 (18.2%)
Driving too fast for conditions1 (9.1%)
Failed to yield right of way1 (9.1%)
Failure to keep in proper lane or running off road1 (9.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Weather conditions for crashes diversified in March 2023, with 4 crashes occurring in clear weather compared to 9 in March 2022, and 2 crashes each in rain and snow, which were not present in the prior period's top conditions. Road surface conditions also showed a shift, with dry road crashes decreasing from 8 to 6, while wet road crashes slightly increased from 2 to 3. Lighting conditions remained predominantly daylight, though 'Dark - roadway not lighted' crashes decreased from 2 to 0, replaced by 1 crash in 'Dark - lighted roadway'.

Weather

Clear4 (36.4%)
-55.6%prior 9
Cloudy3 (27.3%)
Rain2 (18.2%)
Snow2 (18.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Weather condition at time of crash

Lighting

Daylight10 (90.9%)
11.1%prior 9
Dark - lighted roadway1 (9.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Lighting condition field

Road Surface

Dry6 (54.5%)
-25.0%prior 8
Wet3 (27.3%)
Snow2 (18.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (19 vehicles)

1
FORD4 (21.1%)
2
TOYOTA3 (15.8%)
3
CHEVROLET2 (10.5%)
4
HYUNDAI1 (5.3%)
5
JEEP1 (5.3%)
6
KIA1 (5.3%)
7
LEXUS1 (5.3%)
8
LNDR1 (5.3%)
9
NISSAN1 (5.3%)
10
SUBARU1 (5.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Vehicle unit records

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

Sex Distribution (32 persons with recorded sex)

Male17 (53.1%)
112.5%prior 8
Female15 (46.9%)
25.0%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes by speed limit zones shifted, with crashes in the 35 mph zone decreasing from 6 in March 2022 to 2 in March 2023. Conversely, crashes in the 40 mph zone increased from 3 to 7 year-over-year. Additionally, March 2023 saw 1 crash each in 25 mph and 30 mph zones, which were not present in the prior period, while 45 mph zone crashes, which accounted for 2 incidents in March 2022, were absent.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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: 2023-03-01 through 2023-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-03-01 through 2023-03-31 (31 days)
  • Geographic scope: GRANBY, MA
  • Total crash records analyzed: 11
  • Total persons involved: 33
  • Total vehicles involved: 19

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: March 2023." Published June 21, 2026. Reporting period: 2023-03-01 to 2023-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/granby/march-2023-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 — March 2023 | ThatCarHitMe.com