ThatCarHitMe.com
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YEAR-OVER-YEAR CRASH REPORT · AGAWAM, MA · JUNE 2023
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/june-2023-report
Monthly Traffic Safety Analysis
68 CRASHES IN
AGAWAM, MA
JUNE 2023
In June 2023, Agawam experienced 68 crashes, a 33.3% increase compared to 51 crashes in June 2022. Total injuries rose significantly by 81.25%, from 16 to 29. The most notable shift was a 400% increase in hit-and-run crashes, rising from 1 in the prior period to 5 in the current period.
68
▲ 33.3%was 51
Total Crash Events
0
Persons Killed
29
▲ 81.3%was 16
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. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash activity in Agawam increased year-over-year. The total number of crashes rose by 33.3%, from 51 in June 2022 to 68 in June 2023. Concurrently, total injuries increased by 81.25%, from 16 to 29 during the same period.
5
Hit-and-Run Crashes — June 2023
▲ 400.0% vs prior (1)
Hit-and-run incidents increased significantly in June 2023, with 5 crashes reported compared to just 1 in June 2022. This represents a 400% increase in hit-and-run crashes year-over-year. Consequently, the hit-and-run rate also rose from 2% to 7.4% of all crashes.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
28
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak crash hour remained consistent at 5 PM in both June 2022 and June 2023, each recording 11 crashes. However, the peak crash day shifted from Wednesday, with 11 crashes in the prior period, to Thursday, which saw 14 crashes in the current period. There was also a notable increase in crashes on Sunday, rising from 3 to 11, and on Tuesday and Friday, both increasing from 7 to 13 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities and fatal crashes remained at zero in both June 2022 and June 2023. Total injuries increased from 16 to 29 year-over-year. The number of crashes resulting in serious injury (Severity A) decreased from 1 to 0, while minor injuries (Severity B) increased from 6 to 8, and possible injuries (Severity C) increased from 3 to 7.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Most severe injury per crash record
Top Contributing Factors
Several contributing factors saw notable changes year-over-year. Crashes attributed to 'Inattention' increased by 6, from 11 in June 2022 to 17 in June 2023, making it the top factor. 'Followed too closely' crashes rose by 3, from 6 to 9, and 'Failed to yield right of way' increased by 3 crashes, from 4 to 7. Conversely, crashes where 'No improper driving' was cited decreased significantly by 9, from 17 to 8.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring on dry road surfaces increased from 49 in June 2022 to 63 in June 2023, while those on wet surfaces rose from 2 to 5. The number of crashes during clear weather conditions increased from 37 to 43, and cloudy conditions from 9 to 19. Crashes in dark conditions decreased from 9 in the prior period to 7 in the current period.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Road surface condition field
Vehicles & Demographics
The number of vehicles involved in crashes increased from 96 in June 2022 to 134 in June 2023. Among top vehicle makes, Toyota increased from 14 to 20, Ford from 14 to 18, and Hyundai from 6 to 11. The most significant demographic shift was observed in the 0-15 age group, where the number of persons involved in crashes rose from 9 to 53, an increase of 44 persons.
Top Vehicle Makes (134 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Vehicle unit records
16 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (183 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 25 mph speed zone doubled from 9 in June 2022 to 18 in June 2023, representing the largest increase in any single speed zone. Crashes also increased in the 30 mph zone, from 5 to 9, and in the 15 mph zone, from 2 to 5. Conversely, crashes in the 35 mph speed zone decreased from 21 to 17 year-over-year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · 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: 2023-06-01 through 2023-06-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-06-01 through 2023-06-30 (30 days)
- Geographic scope: AGAWAM, MA
- Total crash records analyzed: 68
- Total persons involved: 226
- Total vehicles involved: 134
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: June 2023." Published June 21, 2026. Reporting period: 2023-06-01 to 2023-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/agawam/june-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2023-06-01 – 2023-06-30
Generated: June 21, 2026 · All rights reserved