Tri-State Gimme 5 Results
On Wednesday night, January 14, 2026, the Tri-State Gimme 5 draw in Vermont brought 01 15 19 26 28 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 January 14, 2026 in Vermont.
Draw times: Evening.
Our take on the Tri-State Gimme 5 results
January 14, 2026Tri-State Gimme 5 report — Wednesday night, January 14, 2026: 01 15 19 26 28 shows a notable pattern
On Wednesday night, January 14, 2026, the Tri-State Gimme 5 draw in Vermont brought 01 15 19 26 28 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 Wednesday night, January 14, 2026, the Tri-State Gimme 5 draw in Vermont brought 01 15 19 26 28 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 draw contains 5 distinct numbers with no repeats in the numbers. The numbers run from 1 to 28 with a wide range.
Why Droughts Matter
Extended absences function as context, not a cue - they show where spacing departs from typical cadence. They offer context for distribution stability over time.
Data Notes
This analysis uses the draw results recorded for Wednesday night, January 14, 2026 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
The core idea: these reports are built to preserve a stable long-horizon record as a stable reference point. The priority is accuracy and continuity.
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.
Adding to the Long-Term Record
The return of 01 15 19 26 28 expands the archive by one more data point. It is the accumulation of these entries, not a single draw, that defines the reliability of long-horizon analysis.