Tri-State Gimme 5 Results
On Thursday night, February 19, 2026, the Tri-State Gimme 5 draw in Vermont brought 13 16 27 29 31 back after days away. Given an expected cadence of 1 in 575,757 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 19, 2026 in Vermont.
Draw times: Evening.
Our take on the Tri-State Gimme 5 results
February 19, 2026Tri-State Gimme 5 report — Thursday night, February 19, 2026: 13 16 27 29 31 shows a notable pattern
On Thursday night, February 19, 2026, the Tri-State Gimme 5 draw in Vermont brought 13 16 27 29 31 back after days away. Given an expected cadence of 1 in 575,757 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Overview
On Thursday night, February 19, 2026, the Tri-State Gimme 5 draw in Vermont brought 13 16 27 29 31 back after days away. Given an expected cadence of 1 in 575,757 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Combo Profile
Structurally, this result has 5 distinct numbers with no repeats in the numbers. The range sits at 13 to 31, a wide spread.
Why Droughts Matter
Prolonged absences are best read as context, not forward-looking - they show how distribution tails behave. They clarify how far outcomes drift from baseline cadence.
Data Notes
This analysis uses the draw results recorded for Thursday night, February 19, 2026 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
Simply put: these reports are intended to preserve a stable long-horizon record for analysts and long-run tracking. The priority is accuracy and continuity.
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.
Adding to the Long-Term Record
With its return, 13 16 27 29 31 contributes another meaningful data point to the historical dataset. Each draw - whether routine or statistically unusual - refines the long-term view of how large random systems behave over time.