Tri-State Gimme 5 Results
On Tuesday night, January 13, 2026, 03 11 16 24 27 resurfaced after a -day wait in the Vermont record. Relative to 1 in 575,757 draws, the gap reads as a long-horizon outlier.
Winning numbers for 1 draw on January 13, 2026 in Vermont.
Draw times: Evening.
Our take on the Tri-State Gimme 5 results
January 13, 2026Tri-State Gimme 5 report — Tuesday night, January 13, 2026: 03 11 16 24 27 shows a notable pattern
On Tuesday night, January 13, 2026, 03 11 16 24 27 resurfaced after a -day wait in the Vermont record. Relative to 1 in 575,757 draws, the gap reads as a long-horizon outlier.
Overview
On Tuesday night, January 13, 2026, 03 11 16 24 27 resurfaced after a -day wait in the Vermont record. Relative to 1 in 575,757 draws, the gap reads as a long-horizon outlier.
Combo Profile
As a number shape, this sequence shows 5 distinct numbers with no repeats in the pattern. The spread runs 3 to 27 (wide).
Why Droughts Matter
Deep gaps are context, not predictive - they mark how variance accumulates over long samples. They clarify how far outcomes drift from baseline cadence.
Data Notes
This analysis uses the draw results recorded for Tuesday night, January 13, 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 sustain continuity in the archive as a reliable record for analysts. The aim is a trustworthy record.
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. Context improves with scale. As more draws accumulate, isolated anomalies either normalize into baseline rates or reveal persistent deviations that warrant closer monitoring.
Adding to the Long-Term Record
With its return, 03 11 16 24 27 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.