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YEAR-OVER-YEAR CRASH REPORT · AGAWAM, MA · JANUARY 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/january-2023-report
Monthly Traffic Safety Analysis
44 CRASHES IN
AGAWAM, MA
JANUARY 2023
In January 2023, Agawam experienced a total of 44 crashes, a notable decrease from the 66 crashes reported in January 2022, representing a 33.3% reduction year-over-year. Despite the decrease in total crashes, the number of injuries increased from 8 to 11, marking a 37.5% rise. The most significant year-over-year shift was the overall reduction in total crashes, coupled with an increase in the injury rate per crash.
44
▼ -33.3%was 66
Total Crash Events
0
Persons Killed
11
▲ 37.5%was 8
Persons Injured
8
▲ 33.3%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. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a decrease in total crashes, with 44 crashes in January 2023 compared to 66 crashes in January 2022, a reduction of 33.3%. Conversely, total injuries increased by 37.5%, from 8 in January 2022 to 11 in January 2023. There were no fatalities reported in either period.
8
Hit-and-Run Crashes — January 2023
▲ 33.3% vs prior (6)
Hit-and-run crashes increased from 6 in January 2022 to 8 in January 2023. This resulted in the hit-and-run rate rising from 9.1% of total crashes in the prior period to 18.2% in the current period. The increase indicates a notable upward trend in the proportion of crashes involving a hit-and-run incident.
Vulnerable Road User Casualties
0
Motorists Killed
11
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · 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 Wednesday with 22 crashes in January 2022 to Thursday with 10 crashes in January 2023. The peak hour also changed significantly, moving from 8 AM with 15 crashes in January 2022 to 5 PM with 5 crashes in January 2023. Overall, the distribution of crashes across days of the week and hours of the day shows a less concentrated pattern in the current period compared to the prior period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either January 2023 or January 2022. Total injuries increased from 8 in the prior period to 11 in the current period, a 37.5% increase. Minor injuries (Severity B) saw a substantial increase from 2 (3% of total crashes) to 5 (11.4% of total crashes), while possible injuries (Severity C) decreased from 6 (9.1% of total crashes) to 3 (6.8% of total crashes).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Most severe injury per crash record
Top Contributing Factors
The number of crashes attributed to 'No improper driving' decreased significantly from 34 in January 2022 to 13 in January 2023, a reduction of 21 crashes. 'Inattention' also saw a decrease from 8 crashes to 5 crashes, a reduction of 3. Conversely, 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' increased from 2 crashes to 5 crashes, and 'Failure to keep in proper lane or running off road' increased from 1 crash to 4 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions decreased from 26 in January 2022 to 12 in January 2023. The number of crashes on 'Wet' road surfaces increased from 6 in January 2022 to 17 in January 2023, while crashes on 'Ice' decreased sharply from 21 to 1. Crashes in 'Daylight' conditions decreased from 44 to 22, while crashes in 'Dark - roadway not lighted' conditions increased from 3 to 8.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 114 in January 2022 to 77 in January 2023. Toyota and Ford remained among the top makes involved, though Ford's involvement decreased from 18 to 8, and Toyota's from 15 to 10. The age group 0-15 saw an increase in persons involved, from 9 to 24, while the 65+ age group decreased from 16 to 9. The number of male persons involved decreased from 62 to 52, and female persons from 58 to 40.
Top Vehicle Makes (77 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Vehicle unit records
14 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (92 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 35 mph speed limit zone decreased substantially from 33 in January 2022 to 7 in January 2023. Conversely, crashes in the 25 mph speed limit zone increased from 7 to 11. The number of crashes in the 40 mph zone decreased from 13 to 9, while the 55 mph zone remained constant with 5 crashes in both periods. There were no fatal crashes reported across any speed limit zone in either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · 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: 2023-01-01 through 2023-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-01-31 (31 days)
- Geographic scope: AGAWAM, MA
- Total crash records analyzed: 44
- Total persons involved: 108
- Total vehicles involved: 77
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: January 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/agawam/january-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: 2023-01-01 – 2023-01-31
Generated: June 21, 2026 · All rights reserved