Tri-State Megabucks Results
On Saturday night, February 21, 2026, the Tri-State Megabucks draw in Vermont brought 13 19 30 31 34 back after days away. Given an expected cadence of 1 in 749,398 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Winning numbers for 1 draw on February 21, 2026 in Vermont.
Draw times: Evening.
Our take on the Tri-State Megabucks results
February 21, 2026Tri-State Megabucks report — Saturday night, February 21, 2026: 13 19 30 31 34 shows a notable pattern
On Saturday night, February 21, 2026, the Tri-State Megabucks draw in Vermont brought 13 19 30 31 34 back after days away. Given an expected cadence of 1 in 749,398 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Overview
On Saturday night, February 21, 2026, the Tri-State Megabucks draw in Vermont brought 13 19 30 31 34 back after days away. Given an expected cadence of 1 in 749,398 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Combo Profile
The numbers in 13 19 30 31 34 cover a wide range (13 to 34) with no repeats.
Why Droughts Matter
Extended absences are best treated as context, not a forecast - they document what has already happened. They make variance visible across extended windows.
Data Notes
This analysis uses the draw results recorded for Saturday night, February 21, 2026 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
To be clear: these reports are intended to document distribution behavior over time as a stable reference point. The aim is context, not a call to action.
Additional Context
Long-horizon tracking is the only reliable way to separate short-term noise from persistent drift. By logging each outcome against its expected cadence, the system builds a distribution profile that becomes more stable as the sample grows. Long-horizon tracking is the only reliable way to separate short-term noise from persistent drift. By logging each outcome against its expected cadence, the system builds a distribution profile that becomes more stable as the sample grows.
Adding to the Long-Term Record
From a long-horizon view, 13 19 30 31 34 adds a new point to the dataset to the historical dataset. Long-horizon stability comes from accumulation.