ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WEST SPRINGFIELD, MA · FEBRUARY 2024
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
89 CRASHES IN
WEST SPRINGFIELD, MA
FEBRUARY 2024
WEST SPRINGFIELD experienced a notable increase in total crashes from February 2023 to February 2024, rising from 62 to 89 crashes, a 43.55% increase. Total injuries also saw a substantial increase, from 12 to 27. A significant shift was the emergence of 3 DUI crashes and 2 pedestrian crashes in the current period, compared to none in the prior period.
89
▲ 43.5%was 62
Total Crash Events
0
Persons Killed
27
▲ 125.0%was 12
Persons Injured
12
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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the trend indicates a significant increase in crash activity year-over-year, with total crashes rising from 62 in February 2023 to 89 in February 2024. This represents a 43.55% increase in crashes. Concurrently, total injuries increased by 125%, from 12 in the prior period to 27 in the current period.
12
Hit-and-Run Crashes — February 2024
▼ 0.0% vs prior (12)
The number of hit-and-run crashes remained constant at 12 in both February 2023 and February 2024. However, due to an increase in total crashes, the hit-and-run rate decreased from 19.4% in the prior period to 13.5% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
2
Pedestrians Injured
25
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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 (19 crashes) in February 2023 to Thursday (18 crashes) in February 2024. The peak hour for crashes remained 4 PM in both periods, though the number of crashes at this hour increased from 8 to 17. Monday also saw a notable increase in crashes, rising from 5 to 16 year-over-year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities remained at 0 in both periods. However, injury severity distributions changed, with serious injuries increasing from 0 to 1 and possible injuries rising from 2 to 7. Minor injuries also increased from 7 to 9, contributing to an overall increase in injury-involved crashes from 12 to 27.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to 'No improper driving' increased by 14, from 21 to 35, while 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' saw a rise of 4 crashes, from 1 to 5. 'Inattention' also increased by 3 crashes, from 7 to 10. Conversely, 'Driving too fast for conditions', which accounted for 3 crashes in the prior period, was not among the listed contributing factors in the current period.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in 'Clear' weather conditions increased by 21, from 45 to 66, and 'Cloudy' conditions increased by 9, from 2 to 11. Crashes on 'Dry' road surfaces increased significantly from 44 to 82. In contrast, crashes on 'Wet' road surfaces decreased from 10 to 6, and adverse conditions like 'Ice' and 'Snow' were not reported in the current period, compared to 3 and 2 crashes respectively in the prior period.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 112 to 163 year-over-year. Honda, Toyota, Ford, and Nissan all saw increases in involvement, with Honda and Ford each increasing by 10 vehicles. All age groups experienced an increase in representation among persons involved, with particularly large increases in the 0-15, 16-20, 21-25, 45-54, and 65+ age ranges.
Top Vehicle Makes (163 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Vehicle unit records
27 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (174 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Person-level records linked to crash events
Speed Limit Zones
The number of crashes occurring in a 30 mph speed zone increased from 24 to 42, representing the largest increase in any single speed zone. Crashes in 25 mph zones also saw a notable rise, from 1 to 8. No fatal crashes were recorded in any speed zone during either the current or prior period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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: 2024-02-01 through 2024-02-29
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-02-01 through 2024-02-29 (29 days)
- Geographic scope: WEST SPRINGFIELD, MA
- Total crash records analyzed: 89
- Total persons involved: 205
- Total vehicles involved: 163
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: February 2024." Published June 21, 2026. Reporting period: 2024-02-01 to 2024-02-29. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/west-springfield/february-2024-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: 2024-02-01 – 2024-02-29
Generated: June 21, 2026 · All rights reserved