ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WEST SPRINGFIELD, MA · JANUARY 2025
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
86 CRASHES IN
WEST SPRINGFIELD, MA
JANUARY 2025
Total crashes in West Springfield decreased by 29.5% year-over-year, from 122 crashes in January 2024 to 86 crashes in January 2025. This period also saw a significant 57.5% reduction in total injuries, dropping from 40 to 17. The most notable shift was the overall decrease in crash incidents and associated injuries.
86
▼ -29.5%was 122
Total Crash Events
0
Persons Killed
17
▼ -57.5%was 40
Persons Injured
8
▼ -46.7%was 15
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 · 2025-01-01 to 2025-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash incidents in West Springfield decreased year-over-year, with total crashes falling by 29.5% from 122 to 86. Concurrently, total injuries saw a substantial decrease of 57.5%, from 40 to 17. This indicates a downward trend in both crash frequency and injury severity.
8
Hit-and-Run Crashes — January 2025
▼ -46.7% vs prior (15)
Hit-and-run crashes decreased by 46.7% year-over-year, falling from 15 incidents in January 2024 to 8 in January 2025. The hit-and-run rate also decreased, moving from 12.3% of total crashes in the prior period to 9.3% in the current period. This indicates a downward trend in hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
16
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes remained Friday in both periods, though the number of crashes on Fridays decreased from 22 in January 2024 to 16 in January 2025. The peak hour for crashes shifted from 5 PM with 16 crashes in January 2024 to 11 AM with 10 crashes in January 2025. This change suggests a shift in the most crash-prone time of day.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes or fatalities reported in either January 2024 or January 2025. Total injuries decreased by 57.5%, from 40 to 17. While serious injuries remained constant at 1 crash, minor injuries decreased from 14 to 5 crashes, and possible injuries decreased from 10 to 6 crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor, "No improper driving," decreased by 22 crashes from 53 to 31 year-over-year. "Followed too closely" saw a notable increase in count, rising from 3 crashes in January 2024 to 9 crashes in January 2025, moving from 8th to 3rd in ranking. Conversely, "Inattention" decreased by 6 crashes, from 10 to 4, and "Driving too fast for conditions" decreased by 3 crashes, from 7 to 4.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather decreased from 64 to 57, while crashes on wet road surfaces decreased significantly from 31 to 12. The share of crashes occurring on adverse road surfaces (wet, snow, ice) decreased from 39.3% in January 2024 to 23.3% in January 2025. This indicates a lower proportion of crashes occurring under challenging road conditions.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 223 to 155 year-over-year. Toyota remained the top vehicle make involved, though its count decreased from 28 to 24, while Honda dropped from second to third, with its count decreasing from 24 to 15. The 35-44 age group was the only one to see an increase in persons involved, rising from 43 to 47, while all other age groups experienced decreases.
Top Vehicle Makes (155 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Vehicle unit records
7 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (189 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 MPH speed zone remained the most frequent, decreasing from 53 crashes in January 2024 to 40 crashes in January 2025. Crashes in higher speed zones, such as 55 MPH and 65 MPH, experienced significant reductions, falling from 5 to 1 and 7 to 2 crashes respectively. There were no fatal crashes reported in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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: 2025-01-01 through 2025-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-01-31 (31 days)
- Geographic scope: WEST SPRINGFIELD, MA
- Total crash records analyzed: 86
- Total persons involved: 194
- Total vehicles involved: 155
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: January 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/west-springfield/january-2025-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: 2025-01-01 – 2025-01-31
Generated: June 21, 2026 · All rights reserved