ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · AGAWAM, MA · 2025
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/2025-annual-report
Yearly Traffic Safety Analysis
672 CRASHES IN
AGAWAM, MA
2025
In Agawam, total vehicle crashes decreased slightly from 685 in the prior year to 672 in the current year, a change of -1.9%. While overall crashes and injuries declined, the most notable year-over-year shift was an increase in total fatalities from one to three. This included two pedestrian fatalities in the current period, whereas none were recorded in the prior period.
672
▼ -1.9%was 685
Total Crash Events
3
▲ 200.0%was 1
Persons Killed
158
▼ -10.7%was 177
Persons Injured
64
▼ -14.7%was 75
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 23 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety trends in Agawam show a mixed picture year-over-year. The total number of crashes fell by 1.9% (from 685 to 672), and total injuries decreased by 10.7% (from 177 to 158). However, the number of fatalities increased from one to three during the same period.
64
Hit-and-Run Crashes — 2025
▼ -14.7% vs prior (75)
The number of hit-and-run crashes decreased from 75 in the prior period to 64 in the current period. This represents a downward trend in both count and rate, as the hit-and-run rate fell from 10.9% to 9.5% of all reported crashes year-over-year.
Vulnerable Road User Casualties
2
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
1
Pedestrians Injured
2
Cyclists Injured
153
Motorists Injured
2
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Monday (117 crashes) in the prior period to Friday (120 crashes) in the current period. The 4 p.m. hour remained the peak time for collisions in both years, though the number of crashes during this hour decreased from 84 to 65. Monthly crash distribution saw August emerge as the new peak month with 74 crashes, up from 63 the previous year, while the prior year's peak in October (74 crashes) saw a decline to 53.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes worsened year-over-year, with fatal crashes increasing from one to three, raising the fatal crash rate from 0.15 to 0.45 per 100 crashes. Crashes resulting in serious injuries decreased from 6 to 4. The proportion of crashes involving possible injuries also declined, from 7.4% of all crashes in the prior period to 6.1% in the current period.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
Inattention remained the leading contributing factor, with its count rising from 205 to 213 crashes. The top four primary factors maintained their rankings, but crashes attributed to 'Failed to yield right of way' saw a significant count increase of 28.8%, from 59 to 76 incidents. Conversely, crashes where 'No improper driving' was cited decreased from 125 to 113.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of crashes by lighting conditions was largely consistent year-over-year, with daylight crashes totaling 497 in both periods. There was a notable increase in collisions on adverse road surfaces; crashes on snow or ice rose from 24 in the prior year to 46 in the current year. Correspondingly, crashes on dry roads decreased from 561 to 539.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles most frequently involved in crashes saw a shift; Toyota became the most common make with 172 vehicles, up from 142, supplanting Honda, which decreased from 162 to 131. Ford remained the third-most-common make with an identical count of 137 vehicles in both years. Among persons involved, there was a decrease in the 16-20 age group (from 204 to 171) and an increase in the 65+ age group (from 174 to 192).
Top Vehicle Makes (1,228 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
145 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,397 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crash distribution shifted across speed zones, with incidents in the 35 mph zone decreasing from 171 to 133, while crashes in 25 mph and 40 mph zones increased from 161 to 181 and 115 to 131, respectively. All three fatal crashes in the current year occurred in zones posted at 35 mph (1 crash) or 40 mph (2 crashes). The single fatal crash in the prior year also occurred in a 40 mph zone.
Fatal crashes by zone: 35 mph: 1 of 133 (0.752%) · 40 mph: 2 of 131 (1.527%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: AGAWAM, MA
- Total crash records analyzed: 672
- Total persons involved: 1,550
- Total vehicles involved: 1,228
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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/agawam/2025-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved