ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GRANBY, MA · 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.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/granby/2022-annual-report
Yearly Traffic Safety Analysis
182 CRASHES IN
GRANBY, MA
2022
In 2022, Granby recorded 182 total vehicle crashes, a 23% increase from the 148 crashes reported in 2021. This rise was accompanied by one fatality, compared to zero in the prior year. The most significant year-over-year shift was the 90% increase in total injuries, which rose from 40 in 2021 to 76 in 2022.
182
▲ 23.0%was 148
Total Crash Events
1
Persons Killed
76
▲ 90.0%was 40
Persons Injured
10
▲ 42.9%was 7
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 8 crashes with unreported severity are 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
Traffic crashes in Granby showed a negative trend, with total incidents rising from 148 in 2021 to 182 in 2022, an increase of 23%. This was compounded by a more severe rise in negative outcomes, as total injuries increased by 90% from 40 to 76, and the city recorded one fatal crash after having none in the previous year.
10
Hit-and-Run Crashes — 2022
▲ 42.9% vs prior (7)
Hit-and-run incidents increased in both count and as a percentage of total crashes. The number of hit-and-run crashes rose from 7 in 2021 to 10 in 2022. The hit-and-run rate also trended upward, increasing from 4.7% of all crashes in 2021 to 5.5% in 2022.
Vulnerable Road User Casualties
0
Cyclists Killed
1
Motorists Killed
2
Cyclists Injured
74
Motorists Injured
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
The temporal patterns of crashes shifted between the two years. The peak day for crashes moved from Monday (28 crashes) in 2021 to Saturday (32 crashes) in 2022. Similarly, the peak hour for incidents shifted slightly earlier, from the 3 p.m. hour (17 crashes) in 2021 to the 2 p.m. hour (24 crashes) in 2022.
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 worsened significantly in 2022 compared to 2021. A fatal crash occurred in 2022, resulting in one fatality, whereas 2021 had none. The number of serious injury crashes increased from 3 to 8, and the total number of individuals injured rose from 40 to 76. Consequently, the proportion of all crashes resulting in any injury (from possible to fatal) increased from 20.9% in 2021 to 33.5% in 2022.
Outcome by Severity (Crash Events)
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 saw a shift in ranking year-over-year. In 2022, 'Inattention' was the top factor with 57 crashes, a 42.5% increase in count from its 40 crashes in 2021 when it was the second-ranked factor. 'No improper driving' decreased from being the top factor in 2021 (43 crashes) to the second in 2022 (39 crashes). The count for 'Failed to yield right of way' also increased from 10 to 13 incidents.
Officer-Reported Primary Contributing Cause
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
In 2022, a larger proportion of crashes occurred in clear weather and on dry roads compared to the previous year. Crashes in clear weather constituted 76.9% of the total in 2022, up from 59.5% in 2021. Conversely, crashes on snowy roads decreased from 19 incidents in 2021 to 8 in 2022, and crashes in snowy weather dropped from 13 to 5. The proportion of crashes occurring in daylight remained stable at approximately 67-68% for both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes remained largely consistent, with Toyota, Honda, and Ford being the most frequent in both years. Notably, Honda's involvement increased from 24 vehicles in 2021 to 35 in 2022, tying Toyota for the most common make. Regarding persons involved, the 26-34 age group was the largest in both years, growing from 50 individuals in 2021 to 61 in 2022. The 65+ age group also saw a notable increase in involvement, from 27 persons to 43.
Top Vehicle Makes (280 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
18 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (333 persons with recorded sex)
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
Crashes in 2022 were more concentrated in higher speed zones compared to 2021. The number of crashes in 40 mph zones saw a substantial increase from 37 to 60, and crashes in 35 mph zones rose from 53 to 63. The single fatal crash in 2022 occurred in a 40 mph zone. In contrast, 2021 had no fatal crashes in any speed zone.
Fatal crashes by zone: 40 mph: 1 of 60 (1.667%)
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: GRANBY, MA
- Total crash records analyzed: 182
- Total persons involved: 352
- Total vehicles involved: 280
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: 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/granby/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
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved