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YEAR-OVER-YEAR CRASH REPORT · AGAWAM, MA · OCTOBER 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/october-2025-report
Monthly Traffic Safety Analysis
53 CRASHES IN
AGAWAM, MA
OCTOBER 2025
In October 2025, Agawam experienced 53 crashes, a decrease of 28.4% compared to 74 crashes in October 2024. Total fatalities remained constant at 1 in both periods, while total injuries decreased by 13.0%, from 23 to 20. A notable shift was the increase in DUI-related crashes, which rose from 0 in the prior period to 2 in the current period.
53
▼ -28.4%was 74
Total Crash Events
1
Persons Killed
20
▼ -13.0%was 23
Persons Injured
7
▲ 40.0%was 5
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. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash trends in Agawam show a significant decrease year-over-year, with total crashes falling by 28.4% from 74 to 53. While total fatalities remained stable at 1, the number of injured persons also decreased by 13.0%, from 23 to 20. This indicates a general improvement in safety metrics for the period.
7
Hit-and-Run Crashes — October 2025
▲ 40.0% vs prior (5)
Hit-and-run crashes increased by 2 incidents, rising from 5 in the prior period to 7 in the current period. This increase led to a significant rise in the hit-and-run rate, which climbed from 6.8% of all crashes in the prior period to 13.2% in the current period, indicating an upward trend.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Pedestrians Injured
1
Cyclists Injured
19
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes showed some shifts year-over-year. The peak day for crashes moved from Saturday with 12 incidents in the prior period to Friday, also with 12 incidents, in the current period. While 4 PM remained the peak hour for crashes in both periods, the number of crashes at this hour decreased from 11 in the prior period to 8 in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The number of fatal crashes remained constant at 1 in both periods, but the fatal crash rate increased from 1.35% in the prior period to 1.89% in the current period. Minor injury crashes decreased significantly from 15 (20.3% share) to 6 (11.3% share). Conversely, possible injury crashes saw an increase, rising from 3 (4.1% share) to 8 (15.1% share) year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor, "Inattention," decreased by 10 crashes, from 28 in the prior period to 18 in the current period, though its share only slightly decreased from 37.8% to 34%. Crashes attributed to "No improper driving" also decreased by 6, from 17 to 11. Conversely, "Followed too closely" crashes increased by 2, from 3 to 5, and its share rose from 4.1% to 9.4%, moving it to the third most common factor.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Clear weather conditions remained the predominant factor in both periods, with their share increasing from 90.5% to 94.3% of crashes. Crashes occurring in rainy conditions decreased from 4 to 1, and cloudy conditions decreased from 3 to 2. Road surface conditions also showed a shift towards drier conditions, with crashes on dry roads increasing their share from 91.9% to 98.1%, while crashes on wet surfaces decreased from 5 to 1.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased by 31, from 130 in the prior period to 99 in the current period. Toyota-involved crashes saw a notable decrease of 13, from 19 to 6, while Honda-involved crashes increased by 2, from 10 to 12. The total number of persons involved in crashes also decreased by 27, from 160 to 133, with a significant decrease of 12 persons in the 65+ age group, from 25 to 13.
Top Vehicle Makes (99 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Vehicle unit records
15 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (118 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Person-level records linked to crash events
Speed Limit Zones
The number of crashes in 35 mph zones decreased by 8, from 23 in the prior period to 15 in the current period; however, this zone recorded 1 fatal crash in the current period compared to none previously. Crashes in 40 mph zones remained stable at 11 incidents, but the fatal crash previously recorded in this zone was absent in the current period. Overall, there was a decrease in crashes across most speed limit categories.
Fatal crashes by zone: 35 mph: 1 of 15 (6.667%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · 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: 2025-10-01 through 2025-10-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-10-01 through 2025-10-31 (31 days)
- Geographic scope: AGAWAM, MA
- Total crash records analyzed: 53
- Total persons involved: 133
- Total vehicles involved: 99
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: October 2025." Published June 21, 2026. Reporting period: 2025-10-01 to 2025-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/agawam/october-2025-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: 2025-10-01 – 2025-10-31
Generated: June 21, 2026 · All rights reserved