Tri-State Gimme 5 Results
On Monday night, April 27, 2026 in Vermont, 04 21 25 34 38 came back after a -day wait in Vermont results. The gap is large relative to 1 in 575,757 draws, placing it deep in the tail.
Winning numbers for 1 draw on April 27, 2026 in Vermont.
Draw times: Evening.
Our take on the Tri-State Gimme 5 results
April 27, 2026Tri-State Gimme 5 report — Monday night, April 27, 2026: 04 21 25 34 38 shows a notable pattern
On Monday night, April 27, 2026 in Vermont, 04 21 25 34 38 came back after a -day wait in Vermont results. The gap is large relative to 1 in 575,757 draws, placing it deep in the tail.
Overview
On Monday night, April 27, 2026 in Vermont, 04 21 25 34 38 came back after a -day wait in Vermont results. The gap is large relative to 1 in 575,757 draws, placing it deep in the tail.
Combo Profile
The numbers in 04 21 25 34 38 cover a wide range (4 to 38) with no repeats.
Why Droughts Matter
Extended gaps function as context, not a forecast - they mark how variance accumulates over long samples. They clarify how far outcomes drift from baseline cadence.
Data Notes
The approach: this analysis records the draw results for Monday night, April 27, 2026 with comparison to long-run frequency baselines. It is context-focused, not predictive.
From Stepzero
To be clear: this series is meant to keep a calm, evidence-first record as a reference point for continuity. The priority is accuracy and continuity.
Additional Context
Context improves with scale. As more draws accumulate, isolated anomalies either normalize into baseline rates or reveal persistent deviations that warrant closer monitoring. Context improves with scale. As more draws accumulate, isolated anomalies either normalize into baseline rates or reveal persistent deviations that warrant closer monitoring. Distribution analysis depends on consistent documentation. Each draw updates the record, allowing analysts to test whether deviations persist, reverse, or revert to expected ranges. 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, this result contributes one more record entry to the archive. It is the cumulative record that makes analysis stable.