ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SPRINGFIELD, MA · FEBRUARY 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.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/springfield/february-2026-report
Monthly Traffic Safety Analysis
40 CRASHES IN
SPRINGFIELD, MA
FEBRUARY 2026
In February 2026, Springfield experienced 40 crashes, a substantial decrease compared to the 199 crashes recorded in February 2025. This represents a significant 79.9% reduction in total crashes year-over-year. The most notable shift was the absence of traffic fatalities in February 2026, down from two fatalities in the prior year.
40
▼ -79.9%was 199
Total Crash Events
0
▼ -100.0%was 2
Persons Killed
13
▼ -71.7%was 46
Persons Injured
7
▼ -84.1%was 44
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 · 2026-02-01 to 2026-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a sharp decline in crash incidents, with total crashes falling by 79.9% from 199 in February 2025 to 40 in February 2026. This significant reduction suggests a positive shift in traffic safety for the period.
7
Hit-and-Run Crashes — February 2026
▼ -84.1% vs prior (44)
Hit-and-run incidents decreased significantly year-over-year, with 7 crashes in February 2026 compared to 44 crashes in February 2025. The hit-and-run rate also trended downwards, falling from 22.1% of all crashes in February 2025 to 17.5% in February 2026.
Vulnerable Road User Casualties
0
Motorists Killed
13
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted year-over-year. The peak day for crashes in February 2026 was Sunday with 10 incidents, a change from February 2025 where Friday recorded the highest count with 38 crashes. The peak hour remained 8 AM in both periods, though the count dropped from 18 in February 2025 to 5 in February 2026.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution of crashes improved year-over-year, with no fatal crashes reported in February 2026 compared to 2 fatal crashes in February 2025. The total number of injuries decreased from 46 to 13. Minor injuries accounted for 17.5% of crashes in the current period, up from 11.6% in the prior period, while possible injuries rose from 3% to 5%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Most severe injury per crash record
Top Contributing Factors
Contributing factors saw significant count reductions across the board. 'No improper driving' decreased by 30 crashes (from 35 to 5), 'Driving too fast for conditions' dropped by 24 crashes (from 28 to 4), and 'Failed to yield right of way' decreased by 14 crashes (from 19 to 5). 'Followed too closely' also saw a reduction of 8 crashes, from 17 to 9, while 'Inattention' was a top factor in the prior period with 28 crashes but did not rank among the top factors in the current period.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Clear weather conditions were associated with a higher proportion of crashes in February 2026 (75%) compared to February 2025 (66.8%). While the proportion of crashes occurring in daylight remained stable at approximately 57%, crashes on dry road surfaces increased from 49.7% in February 2025 to 62.5% in February 2026. Conversely, crashes on snow-covered roads decreased from 19.6% to 17.5%, and on icy roads from 14.1% to 5%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased significantly from 377 in February 2025 to 73 in February 2026. Toyota and Honda remained the top two most frequently involved vehicle makes in both periods, although their counts dropped substantially. The peak age groups for persons involved in crashes shifted slightly, with the 35-44 age group (17 persons) and 26-34 age group (15 persons) having the highest counts in the current period, compared to the 26-34 (70 persons) and 21-25 (55 persons) age groups in the prior period.
Top Vehicle Makes (73 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Vehicle unit records
22 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (85 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones changed, with the 55 mph zone accounting for the most crashes in February 2026 (18 crashes), a shift from the 25 mph zone which led in February 2025 with 57 crashes. There were no fatal crashes reported across any speed zone in February 2026, whereas the 30 mph zone recorded 2 fatalities in February 2025.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-02-01 to 2026-02-28 · 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: 2026-02-01 through 2026-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2026-02-01 through 2026-02-28 (28 days)
- Geographic scope: SPRINGFIELD, MA
- Total crash records analyzed: 40
- Total persons involved: 108
- Total vehicles involved: 73
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). "SPRINGFIELD, MA Crash Intelligence Report: February 2026." Published June 21, 2026. Reporting period: 2026-02-01 to 2026-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/springfield/february-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: 2026-02-01 – 2026-02-28
Generated: June 21, 2026 · All rights reserved