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YEAR-OVER-YEAR CRASH REPORT · AGAWAM, MA · MAY 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/may-2025-report
Monthly Traffic Safety Analysis
57 CRASHES IN
AGAWAM, MA
MAY 2025
Total crashes in AGAWAM increased by 21.28%, from 47 in May 2024 to 57 in May 2025. This period also saw a significant shift in crash outcomes, with one fatality recorded in May 2025 compared to zero in the prior year. Additionally, hit-and-run incidents surged, more than doubling year-over-year.
57
▲ 21.3%was 47
Total Crash Events
1
Persons Killed
18
▼ -5.3%was 19
Persons Injured
6
▲ 200.0%was 2
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. 3 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the trend indicates a notable increase in crash incidents, with total crashes rising from 47 to 57, marking a 21.28% increase year-over-year. This upward trend is accompanied by the emergence of fatal crashes, which were absent in the prior period. The number of injured persons remained relatively stable, decreasing slightly from 19 to 18.
6
Hit-and-Run Crashes — May 2025
▲ 200.0% vs prior (2)
Hit-and-run crashes significantly increased year-over-year, rising from 2 incidents in May 2024 to 6 incidents in May 2025. Consequently, the hit-and-run rate also saw a substantial increase, from 4.3% of all crashes in May 2024 to 10.5% in May 2025. This indicates an upward trend in the occurrence and proportion of hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
1
Motorists Killed
1
Pedestrians Injured
17
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Friday in both periods, with 14 crashes in May 2025 compared to 9 in May 2024. Similarly, the peak hour for crashes held steady at 4 PM, increasing from 7 crashes in May 2024 to 11 crashes in May 2025. This indicates a consistent temporal pattern for crash occurrences, albeit with higher volumes in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity saw a significant change, with a fatal crash rate of 1.75% in May 2025, compared to 0% in May 2024. While minor injury crashes decreased in count from 7 to 5, possible injury crashes increased from 4 to 8. The proportion of crashes resulting in no injury decreased from 76.6% to 70.2% year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record
Top Contributing Factors
Several contributing factors showed notable changes in count year-over-year. Crashes attributed to 'Inattention' increased from 15 to 18, while 'Followed too closely' more than doubled, rising from 3 to 9 incidents. 'Failed to yield right of way' also saw a substantial increase, from 5 to 9 crashes, indicating a worsening trend in these specific driving behaviors.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring on wet road surfaces more than doubled, increasing from 9 in May 2024 to 20 in May 2025, despite a decrease in clear weather crashes from 31 to 29. While daylight conditions remained dominant, crashes occurring in 'Dark - lighted roadway' conditions decreased from 8 to 3. This suggests a shift towards more crashes occurring during adverse road conditions.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 90 to 110 year-over-year. Among top makes, Toyota and Ford were tied for the highest number of vehicles involved in May 2025 with 12 each, a slight shift from May 2024 where Ford and Honda shared the top spot with 12 vehicles each. In terms of persons, there was a notable increase in persons aged 16-20 (from 13 to 20) and 35-44 (from 15 to 26) involved in crashes.
Top Vehicle Makes (110 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records
16 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (123 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 40 mph speed zones increased from 9 in May 2024 to 13 in May 2025, with this zone recording the only fatal crash in the current period. Crashes in 25 mph zones decreased from 17 to 13, while those in 35 mph zones nearly tripled, from 4 to 11. This indicates a shift in crash distribution across different speed limit areas, with a concentration increase in 35 mph and 40 mph zones.
Fatal crashes by zone: 40 mph: 1 of 13 (7.692%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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: 2025-05-01 through 2025-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-05-01 through 2025-05-31 (31 days)
- Geographic scope: AGAWAM, MA
- Total crash records analyzed: 57
- Total persons involved: 143
- Total vehicles involved: 110
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: May 2025." Published June 21, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/agawam/may-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: 2025-05-01 – 2025-05-31
Generated: June 21, 2026 · All rights reserved