Tri-State Gimme 5 Results
On Tuesday night, March 24, 2026, the Tri-State Gimme 5 draw in Vermont brought 15 18 24 28 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 March 24, 2026 in Vermont.
Draw times: Evening.
Our take on the Tri-State Gimme 5 results
March 24, 2026Tri-State Gimme 5 report — Tuesday night, March 24, 2026: 15 18 24 28 31 shows a notable pattern
On Tuesday night, March 24, 2026, the Tri-State Gimme 5 draw in Vermont brought 15 18 24 28 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 Tuesday night, March 24, 2026, the Tri-State Gimme 5 draw in Vermont brought 15 18 24 28 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 sequence uses 5 distinct numbers with no repeats noted. The range sits at 15 to 31, a wide spread.
Why Droughts Matter
Extended gaps are best treated as context, not forward-looking - they show how distribution tails behave. They clarify how far outcomes drift from baseline cadence.
Data Notes
In detail: this analysis documents the draw results for Tuesday night, March 24, 2026 and evaluates them against long-run frequency baselines. This is descriptive, not predictive.
From Stepzero
The takeaway: this reporting is built to document distribution behavior over time as a calm, evidence-first reference. The aim is a trustworthy record.
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.
Distribution analysis depends on consistent documentation. Each draw updates the record, allowing analysts to test whether deviations persist, reverse, or revert to expected ranges.
Distribution analysis depends on consistent documentation. Each draw updates the record, allowing analysts to test whether deviations persist, reverse, or revert to expected ranges.
Adding to the Long-Term Record
Over the broader record, this entry adds another data point to the record. Reliability is a function of the growing record.