ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · AGAWAM, MA · 2022
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/2022-annual-report
Yearly Traffic Safety Analysis
661 CRASHES IN
AGAWAM, MA
2022
In 2022, Agawam recorded 661 total traffic crashes, a 2.3% increase from the 646 crashes documented in 2021. Despite the rise in total incidents, the number of people injured decreased by 18.7%, from 214 to 174. The most significant year-over-year shift was a reduction in crashes categorized with 'Possible Injury,' which fell from 89 incidents in 2021 to 63 in 2022.
661
▲ 2.3%was 646
Total Crash Events
2
▼ -33.3%was 3
Persons Killed
174
▼ -18.7%was 214
Persons Injured
46
▲ 17.9%was 39
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 40 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the total number of crashes in Agawam trended slightly upward, increasing by 15 incidents from 646 in 2021 to 661 in 2022. However, this increase in crash volume was accompanied by a decrease in severity. The number of individuals killed fell from 3 to 2, and total injuries dropped from 214 to 174 year-over-year.
46
Hit-and-Run Crashes — 2022
▲ 17.9% vs prior (39)
7.0% hit-and-run rate this period vs 6.0% prior. Prior period: 39.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
2
Motorists Killed
0
Other Killed
1
Pedestrians Injured
3
Cyclists Injured
169
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed a slight shift between the two periods. In 2022, the peak day for crashes was Wednesday with 112 incidents, whereas in 2021 it was Thursday with 107. The peak hour also shifted one hour later, from 4 p.m. in 2021 (68 crashes) to 5 p.m. in 2022 (83 crashes), indicating the afternoon commute remains the highest-risk time of day.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity decreased from 2021 to 2022. The number of fatal crashes fell from 3 to 2, and the corresponding fatal crash rate dropped from 0.46% to 0.3%. While the count of serious injury crashes remained stable at 8 for both years, the number of 'Possible Injury' crashes decreased from 89 to 63. Consequently, the proportion of non-injury crashes increased from 70.9% of all incidents in 2021 to 74.6% in 2022.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The top three contributing factors remained consistent across both years: 'Inattention,' 'Followed too closely,' and 'Failed to yield right of way.' The count of crashes attributed to 'Inattention' rose slightly from 140 to 146. In contrast, the count for 'Followed too closely' decreased from 96 to 71, and 'Failed to yield right of way' incidents fell from 66 to 64. 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' saw its count double from 11 in 2021 to 22 in 2022.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in 2022 occurred under slightly more favorable conditions compared to 2021. The proportion of crashes on wet road surfaces decreased from 15.3% in 2021 to 10.6% in 2022. Similarly, incidents during 'Dark - lighted roadway' conditions fell from 22.1% of all crashes in 2021 to 17.8% in 2022. The share of crashes occurring in clear weather and on dry roads remained the dominant condition in both years, with slight proportional increases in 2022.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes were Toyota, Ford, and Honda in both years, with their order shifting slightly. In 2022, Ford (147 vehicles) surpassed Honda (135 vehicles) for the second position, while Toyota remained first despite its count decreasing from 165 to 153. The age distribution of persons involved in crashes was very stable, with the 26-34 age group representing the largest cohort in both 2021 (256 people) and 2022 (249 people).
Top Vehicle Makes (1,212 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
131 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,321 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
There was a noticeable shift in where crashes occurred by speed zone. Crashes in 35 mph zones increased from 189 in 2021 to 251 in 2022, while incidents in 25 mph zones decreased from 146 to 126. Fatal crashes also shifted; in 2021, two fatal crashes occurred in 35 mph zones and one in a 45 mph zone, whereas in 2022, one fatal crash occurred in a 35 mph zone and one in a 40 mph zone.
Fatal crashes by zone: 35 mph: 1 of 251 (0.398%) · 40 mph: 1 of 90 (1.111%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: AGAWAM, MA
- Total crash records analyzed: 661
- Total persons involved: 1,487
- Total vehicles involved: 1,212
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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/agawam/2022-annual-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: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved