ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · AGAWAM, MA · MAY 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/may-2023-report
Monthly Traffic Safety Analysis
55 CRASHES IN
AGAWAM, MA
MAY 2023
In May 2023, Agawam experienced 55 crashes, a slight increase from the 54 crashes reported in May 2022, representing a 1.85% rise. The most notable shift was the complete absence of fatalities in May 2023, compared to one fatality in May 2022. Total injuries, however, increased by 25% from 16 to 20.
55
▲ 1.9%was 54
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
20
▲ 25.0%was 16
Persons Injured
7
▲ 16.7%was 6
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, total crashes in Agawam remained relatively stable year-over-year, with a minor increase of 1 crash, or 1.85%, from 54 in May 2022 to 55 in May 2023. Despite this slight rise in crash count, the number of fatalities decreased significantly, from 1 in May 2022 to 0 in May 2023. Conversely, total injuries saw an increase of 4, rising from 16 to 20.
7
Hit-and-Run Crashes — May 2023
▲ 16.7% vs prior (6)
Hit-and-run crashes increased from 6 incidents in May 2022 to 7 incidents in May 2023. The hit-and-run rate also saw an increase, rising from 11.1% of total crashes in May 2022 to 12.7% in May 2023. This represents a 1.6 percentage point increase in the hit-and-run crash rate.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
19
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted between the two periods. In May 2023, the peak day for crashes was Monday with 11 incidents, while in May 2022, Thursday was the peak day with 12 incidents. The peak crash hour also changed, moving from 5 PM with 9 crashes in May 2022 to 3 PM with 8 crashes in May 2023.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes decreased from 1 (1.9% of total crashes) in May 2022 to 0 in May 2023, resulting in a 100% reduction in the fatal crash rate. Total injuries, however, increased by 25%, from 16 in May 2022 to 20 in May 2023. The proportion of minor injuries (severity B) increased from 7.4% to 12.7%, and possible injuries (severity C) increased from 11.1% to 12.7% of total crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Most severe injury per crash record
Top Contributing Factors
Inattention became the leading contributing factor in May 2023 with 16 crashes, up from 10 crashes in May 2022, representing a 60% increase in count. No improper driving decreased from 19 crashes to 11 crashes, dropping from the top factor to second place. Followed too closely saw a 25% increase in count, rising from 8 crashes in May 2022 to 10 crashes in May 2023.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Clear weather remained the dominant condition for crashes, increasing from 38 incidents in May 2022 to 42 in May 2023. Crashes occurring in cloudy conditions decreased from 11 to 8, while crashes in rainy conditions remained stable at 2 incidents. Daylight continued to be the predominant lighting condition, with 50 crashes in May 2023 compared to 41 in May 2022.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 102 in May 2022 to 108 in May 2023. Ford vehicles were involved in 20 crashes in May 2023, a significant increase from 7 in May 2022, making it the top make. Toyota involvement decreased from 18 to 10, while Honda involvement slightly increased from 9 to 10. The age group 55-64 saw the highest number of persons involved in May 2023 with 21, up from 14 in May 2022.
Top Vehicle Makes (108 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records
11 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (121 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 40 mph speed limit zone increased from 6 in May 2022 to 8 in May 2023, while crashes in the 55 mph zone decreased from 9 to 4. The 35 mph speed limit zone saw a slight decrease from 16 crashes to 15. Notably, the single fatal crash in May 2022 occurred in a 40 mph speed limit zone, whereas no fatal crashes were reported in any speed zone in May 2023.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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: 2023-05-01 through 2023-05-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-05-01 through 2023-05-31 (31 days)
- Geographic scope: AGAWAM, MA
- Total crash records analyzed: 55
- Total persons involved: 136
- Total vehicles involved: 108
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 2023." Published June 21, 2026. Reporting period: 2023-05-01 to 2023-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/agawam/may-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: 2023-05-01 – 2023-05-31
Generated: June 21, 2026 · All rights reserved