ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · EAST LONGMEADOW, MA · FEBRUARY 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
21 CRASHES IN
EAST LONGMEADOW, MA
FEBRUARY 2025
In East Longmeadow, February 2025 saw a slight increase in total crashes, rising by 5% from 20 crashes in February 2024 to 21 crashes. This period also experienced a notable 66.7% increase in total injuries, climbing from 3 to 5, despite no fatalities in either period. The most significant shift was in contributing factors, with 'No improper driving' becoming the leading factor.
21
▲ 5.0%was 20
Total Crash Events
0
Persons Killed
5
▲ 66.7%was 3
Persons Injured
1
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 · 2025-02-01 to 2025-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a slight increase in crash volume, with total crashes rising from 20 in February 2024 to 21 in February 2025, representing a 5% increase. Total injuries saw a more substantial rise, increasing by 66.7% from 3 to 5. There were no fatalities reported in either period.
1
Hit-and-Run Crashes — February 2025
▼ 0.0% vs prior (1)
The number of hit-and-run crashes remained consistent at 1 for both February 2024 and February 2025. Consequently, the hit-and-run rate slightly decreased from 5% of total crashes in the prior period to 4.8% in the current period, reflecting the overall increase in total crashes.
Vulnerable Road User Casualties
0
Motorists Killed
5
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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 Thursday in February 2024 (6 crashes) to Tuesday in February 2025 (7 crashes). The peak hour for crashes also saw a minor shift, with both periods recording 3 crashes during their respective peak hours, moving from 5 p.m. in the prior period to 6 p.m. in the current period. Crashes on Thursday significantly decreased from 6 to 1, while crashes on Tuesday increased from 2 to 7.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes or fatalities in either February 2024 or February 2025. Total injuries increased from 3 in the prior period to 5 in the current period. The proportion of crashes resulting in a Minor Injury (code B) increased from 0% in February 2024 to 4.8% in February 2025, while the share of crashes with No Injury decreased from 85% to 81%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor shifted from 'Failed to yield right of way' (7 crashes, 35% share) in February 2024 to 'No improper driving' (7 crashes, 33.3% share) in February 2025. Crashes attributed to 'No improper driving' increased by 4, from 3 to 7, while 'Failed to yield right of way' crashes decreased by 4, from 7 to 3. 'Inattention' also saw a notable increase, rising from 1 crash (5% share) to 3 crashes (14.3% share).
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring on dry road surfaces increased from 11 in February 2024 to 16 in February 2025, while crashes on wet road surfaces decreased from 8 to 2. Snow-related weather conditions, including 'Snow' and 'Cloudy/Blowing sand, snow,' which were absent in February 2024, accounted for 3 crashes in February 2025. The number of crashes in 'Daylight' conditions remained consistent at 12 for both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Road surface condition field
Vehicles & Demographics
Top Vehicle Makes (37 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Vehicle unit records
3 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (38 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph and 35 mph zones remained the most frequent, with 8 and 9 crashes respectively in both periods. There was a shift in other speed zones, with crashes in 20 mph and 45 mph zones (1 each in February 2024) no longer appearing in February 2025. Conversely, crashes in 30 mph and 40 mph zones, which were absent in the prior period, accounted for 2 and 1 crashes respectively in the current period. No fatal crashes were recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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: 2025-02-01 through 2025-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-02-01 through 2025-02-28 (28 days)
- Geographic scope: EAST LONGMEADOW, MA
- Total crash records analyzed: 21
- Total persons involved: 41
- Total vehicles involved: 37
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). "EAST LONGMEADOW, MA Crash Intelligence Report: February 2025." Published June 21, 2026. Reporting period: 2025-02-01 to 2025-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/east-longmeadow/february-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: 2025-02-01 – 2025-02-28
Generated: June 21, 2026 · All rights reserved