ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GRANBY, MA · 2024
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/2024-annual-report
Yearly Traffic Safety Analysis
185 CRASHES IN
GRANBY, MA
2024
In 2024, Granby recorded 185 total traffic crashes, an increase from the 174 crashes reported in 2023, representing a 6.3% rise. While overall crashes increased, the number of fatalities fell from one in the prior year to zero in the current period. Notably, crashes involving a hit-and-run decreased from 11 in 2023 to 4 in 2024.
185
▲ 6.3%was 174
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
74
▲ 5.7%was 70
Persons Injured
4
▼ -63.6%was 11
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. 6 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic crashes in Granby showed a slight upward trend, increasing by 6.3% from 174 in 2023 to 185 in 2024. The total number of injuries also rose modestly from 70 to 74. However, traffic fatalities decreased, with zero reported in 2024 compared to one fatality in the previous year.
4
Hit-and-Run Crashes — 2024
▼ -63.6% vs prior (11)
Hit-and-run incidents decreased significantly in 2024 compared to the prior year. The total count of hit-and-run crashes fell from 11 in 2023 to 4 in 2024, a 63.6% reduction. Consequently, the hit-and-run rate, or the percentage of total crashes that were hit-and-runs, dropped from 6.3% to 2.2%.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
1
Cyclists Injured
72
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained somewhat consistent year-over-year, with Thursday being the peak day for crashes in both 2023 (32 crashes) and 2024 (33 crashes). However, the peak hour for collisions shifted two hours earlier, from 5 p.m. in 2023 to 3 p.m. in 2024, with both hours recording 18 crashes in their respective years. Crashes on Mondays saw a notable increase, rising from 17 in the prior year to 30 in the current year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity decreased in 2024 compared to the previous year. The city recorded zero fatal crashes in 2024, down from one fatal crash in 2023. While the number of serious injury crashes increased from 2 to 4, the overall proportion of crashes resulting in any injury (serious, minor, or possible) decreased. The share of non-injury crashes grew from 63.2% of all incidents in 2023 to 68.6% in 2024.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
Inattention remained the top contributing factor for crashes in both periods, though its count decreased slightly from 54 incidents in 2023 to 52 in 2024. The count for crashes where 'No improper driving' was cited increased from 39 to 50. Notably, crashes attributed to 'Failed to yield right of way' increased by 33.3%, from a count of 12 incidents in 2023 to 16 in 2024. Conversely, crashes involving 'Failure to keep in proper lane or running off road' decreased from a count of 7 to 4.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The majority of crashes in both 2023 and 2024 occurred in clear weather on dry roads during daylight hours. However, there was a notable increase in crashes under adverse winter conditions. The count of crashes on snow or ice rose from 8 in 2023 to 20 in 2024. This corresponds to an increase in the share of total crashes occurring on snow or ice, from 4.6% in the prior year to 10.8% in the current year.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes shifted between the two periods. In 2023, the top makes were Ford (39), Toyota (32), and Honda (30). In 2024, Toyota (44) and Honda (41) surpassed Ford (40) to become the top two. Analysis of persons involved in crashes shows a demographic shift, with the 21-25 age group's involvement increasing from 30 individuals in 2023 to 51 in 2024. Conversely, involvement for the 65+ age group decreased from 52 to 43 persons.
Top Vehicle Makes (291 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
19 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (345 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones saw some changes between the two years. The single fatality in 2023 occurred in a 35 mph zone; no fatalities were recorded in 2024. While the 35 mph and 40 mph zones remained the most common locations for crashes in both periods, the number of crashes in 45 mph zones doubled, increasing from 12 in 2023 to 24 in 2024. In contrast, crashes in 30 mph zones decreased from 21 to 15.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: GRANBY, MA
- Total crash records analyzed: 185
- Total persons involved: 367
- Total vehicles involved: 291
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/granby/2024-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: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved