ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WEST SPRINGFIELD, MA · APRIL 2026
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.
Monthly Traffic Safety Analysis
87 CRASHES IN
WEST SPRINGFIELD, MA
APRIL 2026
In April 2026, West Springfield recorded 87 crashes, a 4.82% increase from the 83 crashes reported in April 2025. Total injuries increased by 42.86%, rising from 14 to 20 over the year. Hit-and-run crashes also saw a significant increase, growing by 44.44% from 9 to 13 incidents.
87
▲ 4.8%was 83
Total Crash Events
0
Persons Killed
20
▲ 42.9%was 14
Persons Injured
13
▲ 44.4%was 9
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.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in West Springfield increased year-over-year, with 87 crashes in April 2026 compared to 83 in April 2025, representing a 4.82% rise. This indicates an upward trend in crash incidents for the specified period. Total injuries also increased, from 14 to 20, a 42.86% rise.
13
Hit-and-Run Crashes — April 2026
▲ 44.4% vs prior (9)
Hit-and-run crashes increased by 4 incidents, from 9 in April 2025 to 13 in April 2026. This resulted in an increase in the hit-and-run rate from 10.8% to 14.9%, indicating an upward trend of 4.1 percentage points year-over-year.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
1
Cyclists Injured
19
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · 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 Tuesday with 17 incidents in April 2025 to Friday with 19 incidents in April 2026. The peak hour for crashes also changed, moving from 12 p.m. with 10 crashes in the prior period to 4 p.m. with 14 crashes in the current period, indicating a shift in the busiest time for incidents.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes or fatalities in either April 2026 or April 2025. Total injuries increased from 14 in the prior period to 20 in the current period, a 42.86% rise. While minor injuries (code B) increased from 4 to 9, and possible injuries (code C) increased from 6 to 7, serious injuries (code A) were reported in the prior period (3 incidents) but not in the current period.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Most severe injury per crash record
Top Contributing Factors
The number of crashes where 'No improper driving' was cited decreased by 1, from 27 to 26 incidents. 'Failed to yield right of way' also decreased by 1 crash, from 15 to 14. 'Followed too closely' saw a decrease of 4 crashes, from 10 to 6, while 'Inattention' increased by 1 crash, from 5 to 6. 'Failure to keep in proper lane or running off road' decreased by 4 crashes, from 9 to 5.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased from 56 to 70 year-over-year, while those in 'Rain' decreased from 9 to 4, and 'Cloudy' conditions decreased from 12 to 3. The number of crashes occurring in 'Daylight' increased from 64 to 76, and crashes on 'Dry' road surfaces increased from 67 to 77. Conversely, crashes on 'Wet' road surfaces decreased from 16 to 8.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 157 in April 2025 to 176 in April 2026. Toyota became the most frequently involved vehicle make in April 2026 with 32 vehicles, up from 14 in April 2025, surpassing Subaru which was tied for first in the prior period. The number of persons aged 35-44 involved in crashes increased by 11, from 24 to 35, while those aged 45-54 decreased by 10, from 32 to 22. There was an '0-15' age group with 13 persons in the current period that was not present in the prior period's age distribution.
Top Vehicle Makes (176 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Vehicle unit records
16 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (199 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph zones increased by 6, from 35 to 41, and in 40 mph zones increased by 5, from 18 to 23. Crashes in 25 mph zones increased by 4, from 7 to 11. Conversely, crashes in 35 mph zones decreased by 4, from 5 to 1. No fatal crashes were reported in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · 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: 2026-04-01 through 2026-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2026-04-01 through 2026-04-30 (30 days)
- Geographic scope: WEST SPRINGFIELD, MA
- Total crash records analyzed: 87
- Total persons involved: 213
- Total vehicles involved: 176
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). "WEST SPRINGFIELD, MA Crash Intelligence Report: April 2026." Published June 21, 2026. Reporting period: 2026-04-01 to 2026-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/west-springfield/april-2026-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: 2026-04-01 – 2026-04-30
Generated: June 21, 2026 · All rights reserved