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YEAR-OVER-YEAR CRASH REPORT · AGAWAM, MA · FEBRUARY 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/february-2023-report
Monthly Traffic Safety Analysis
41 CRASHES IN
AGAWAM, MA
FEBRUARY 2023
Total crashes in AGAWAM, MA increased by 13.9% year-over-year, rising from 36 in February 2022 to 41 in February 2023. Despite this increase in crash incidents, total injuries decreased by 55.6%, falling from 9 to 4. A notable shift was the doubling of hit-and-run crashes, which increased from 3 to 6, with the hit-and-run rate rising from 8.3% to 14.6% of all crashes. The most frequent contributing factor changed from 'Followed too closely' to 'No improper driving' year-over-year.
41
▲ 13.9%was 36
Total Crash Events
0
Persons Killed
4
▼ -55.6%was 9
Persons Injured
6
▲ 100.0%was 3
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 · 2023-02-01 to 2023-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in AGAWAM, MA showed an upward trend, increasing by 13.9% from 36 crashes in February 2022 to 41 crashes in February 2023. In contrast, the number of total injuries significantly decreased by 55.6%, from 9 to 4 over the same period. Fatalities remained stable at zero for both February 2022 and February 2023.
6
Hit-and-Run Crashes — February 2023
▲ 100.0% vs prior (3)
Hit-and-run crashes increased by 100% year-over-year, rising from 3 incidents in February 2022 to 6 incidents in February 2023. The hit-and-run rate also increased from 8.3% of all crashes in the prior period to 14.6% in the current period. This indicates an upward trend in both the count and proportion of hit-and-run incidents.
Vulnerable Road User Casualties
0
Motorists Killed
4
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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 Friday with 7 incidents in February 2022 to Thursday with 8 incidents in February 2023. While 5 p.m. was a peak hour in February 2022 with 5 crashes, the peak hour in February 2023 was 3 p.m., also with 5 crashes. Crashes on Monday, Tuesday, Wednesday, and Thursday were more frequent in the current period compared to the prior period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes or fatalities reported in either February 2022 or February 2023. Total injuries decreased by 55.6%, from 9 in February 2022 to 4 in February 2023. The proportion of crashes resulting in minor injury decreased from 5.6% to 2.4%, and possible injury crashes decreased from 13.9% to 7.3% year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to 'No improper driving' increased by 166.7%, from 6 in February 2022 to 16 in February 2023, making it the most frequent contributing factor. Conversely, 'Followed too closely' crashes decreased by 75%, from 8 to 2, dropping from the top factor to third. 'Inattention' crashes increased by 85.7%, from 7 to 13, maintaining its position as the second most common factor.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased from 19 to 22, while those in 'Rain' conditions decreased from 4 to 1. Crashes on 'Ice' road surfaces increased from 1 to 4, and those on 'Snow' surfaces (including 'Slush' in prior data) increased from 1 to 4. Crashes during 'Daylight' increased from 20 to 26, and those in 'Dark - lighted roadway' conditions increased from 8 to 12.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes remained nearly constant, with 64 in February 2022 and 65 in February 2023. FORD vehicles moved from the third most involved make with 8 incidents to the first with 9 incidents. HONDA and HYUNDAI, previously the top two makes with 9 incidents each, both saw a decrease to 7 incidents in the current period, shifting their rankings.
Top Vehicle Makes (65 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Vehicle unit records
17 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (66 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · Person-level records linked to crash events
Speed Limit Zones
The 35 mph speed zone remained the most frequent location for crashes, with 16 crashes in February 2022 and 17 crashes in February 2023. Crashes in the 30 mph zone decreased from 3 to 1, and in the 40 mph zone decreased from 6 to 4. Conversely, crashes in the 10 mph zone increased from 2 to 3, and in the 25 mph zone increased from 7 to 8.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-02-01 to 2023-02-28 · 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: 2023-02-01 through 2023-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-02-01 through 2023-02-28 (28 days)
- Geographic scope: AGAWAM, MA
- Total crash records analyzed: 41
- Total persons involved: 80
- Total vehicles involved: 65
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: February 2023." Published June 21, 2026. Reporting period: 2023-02-01 to 2023-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/agawam/february-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: 2023-02-01 – 2023-02-28
Generated: June 21, 2026 · All rights reserved