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YEAR-OVER-YEAR CRASH REPORT · AGAWAM, MA · JULY 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/agawam/july-2022-report
Monthly Traffic Safety Analysis
66 CRASHES IN
AGAWAM, MA
JULY 2022
Total crashes in AGAWAM decreased by 9.6% year-over-year, from 73 crashes in July 2021 to 66 crashes in July 2022. This period saw a significant positive shift in safety outcomes, with fatalities dropping from 1 to 0 and total injuries decreasing from 31 to 9. The most notable year-over-year shift is the complete elimination of crash-related fatalities.
66
▼ -9.6%was 73
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
9
▼ -71.0%was 31
Persons Injured
5
▲ 400.0%was 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. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash data for AGAWAM shows a positive trend year-over-year, with total crashes decreasing by 9.6%, from 73 in July 2021 to 66 in July 2022. Total injuries experienced a substantial decline of 70.97%, falling from 31 to 9. Furthermore, the city recorded zero fatalities in July 2022, a reduction from one fatality in July 2021.
5
Hit-and-Run Crashes — July 2022
▲ 400.0% vs prior (1)
Hit-and-run crashes saw a substantial increase year-over-year, rising from 1 crash in July 2021 to 5 crashes in July 2022. Consequently, the hit-and-run rate increased from 1.4% of total crashes in July 2021 to 7.6% in July 2022.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
8
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · 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 moving from Monday (14 crashes) in July 2021 to Sunday (15 crashes) in July 2022. The peak crash hour also changed, moving from 4 p.m. (10 crashes) in July 2021 to 9 p.m. (8 crashes) in July 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity saw significant improvements year-over-year. Fatal crashes decreased from 1 in July 2021 to 0 in July 2022, and total injuries dropped from 31 to 9. The number of minor injuries (severity B) decreased from 10 to 3, while possible injuries (severity C) decreased from 8 to 4.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'Followed too closely' crashes decreased by 8, from 16 in July 2021 to 8 in July 2022, representing a 50% reduction in count. Conversely, 'Inattention' crashes increased by 3, from 15 in July 2021 to 18 in July 2022. 'No improper driving' also saw an increase of 4 crashes, from 12 to 16.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Weather conditions at the time of crashes shifted, with crashes occurring in 'Clear' conditions increasing from 35 in July 2021 to 53 in July 2022, while crashes in 'Cloudy' conditions decreased from 17 to 4. Crashes on 'Wet' road surfaces significantly decreased from 17 to 1 year-over-year. In terms of lighting, crashes during 'Daylight' hours decreased from 59 to 48, while crashes in 'Dark - lighted roadway' conditions increased from 7 to 11.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 145 in July 2021 to 132 in July 2022. The top vehicle makes involved also shifted, with Toyota moving from the top spot (28 vehicles) in July 2021 to fifth (10 vehicles) in July 2022, while Ford rose to the top with 20 vehicles. Regarding persons involved, the 26-34 age group saw a decrease from 40 to 23 persons, and the 0-15 age group decreased from 17 to 9 persons.
Top Vehicle Makes (132 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Vehicle unit records
20 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (143 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 35 mph speed limit zone decreased slightly from 23 to 21, notably with fatalities in this zone dropping from 1 to 0. Crashes in the 25 mph zone decreased from 17 to 13, and in the 40 mph zone from 17 to 11. Conversely, crashes in the 55 mph speed limit zone increased from 3 to 7.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-07-01 to 2022-07-31 · 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: 2022-07-01 through 2022-07-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-07-01 through 2022-07-31 (31 days)
- Geographic scope: AGAWAM, MA
- Total crash records analyzed: 66
- Total persons involved: 165
- Total vehicles involved: 132
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). "AGAWAM, MA Crash Intelligence Report: July 2022." Published June 21, 2026. Reporting period: 2022-07-01 to 2022-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/agawam/july-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: 2022-07-01 – 2022-07-31
Generated: June 21, 2026 · All rights reserved