Tri-State Gimme 5 Results
On Tuesday night, February 3, 2026, the Tri-State Gimme 5 draw in Vermont brought 02 03 18 33 39 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 3, 2026 in Vermont.
Draw times: Evening.
Our take on the Tri-State Gimme 5 results
February 3, 2026Tri-State Gimme 5 report — Tuesday night, February 3, 2026: 02 03 18 33 39 shows a notable pattern
On Tuesday night, February 3, 2026, the Tri-State Gimme 5 draw in Vermont brought 02 03 18 33 39 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 Tuesday night, February 3, 2026, the Tri-State Gimme 5 draw in Vermont brought 02 03 18 33 39 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
From a number-profile view, the pattern settles on 5 distinct numbers with no repeats noted. The numbers run from 2 to 39 with a wide range.
Why Droughts Matter
Prolonged absences are context, not a signal - they show how distribution tails behave. They make variance visible across extended windows.
Data Notes
The method: this report summarizes the recorded draws for Tuesday night, February 3, 2026 with comparison to long-run frequency baselines. The intent is documentation, not forecasting.
From Stepzero
Importantly: these reports are intended to keep the record consistent over time as context for disciplined analysis. It is meant to inform, not forecast.
Additional Context
Long-horizon measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges.
Long-horizon measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges.
Long-horizon measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges.
Adding to the Long-Term Record
Over the long run, this return adds a fresh entry to the record to the long-horizon record. Reliability is a function of the growing record.