Tri-State Gimme 5 Results
On Wednesday night, January 28, 2026, the Tri-State Gimme 5 draw in New Hampshire marked a notable return: 04 14 16 32 37 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 575,757 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Winning numbers for 1 draw on January 28, 2026 in New Hampshire.
Draw times: Evening.
Our take on the Tri-State Gimme 5 results
January 28, 2026Tri-State Gimme 5 report — Wednesday night, January 28, 2026: 04 14 16 32 37 shows a notable pattern
On Wednesday night, January 28, 2026, the Tri-State Gimme 5 draw in New Hampshire marked a notable return: 04 14 16 32 37 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 575,757 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Overview
On Wednesday night, January 28, 2026, the Tri-State Gimme 5 draw in New Hampshire marked a notable return: 04 14 16 32 37 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 575,757 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Combo Profile
As a number pattern, 04 14 16 32 37 uses 5 distinct numbers and a wide spread from 4 to 37.
Why Droughts Matter
Deep gaps are best treated as context, not a cue - they highlight the tail behavior of the system. Their value is in long-horizon tracking.
Data Notes
This report summarizes observed outcomes for Wednesday night, January 28, 2026 and interprets them within the long-run distribution record. It does not imply a forecast or recommendation.
From Stepzero
In summary: this series is designed to keep the record consistent over time as a reference point for continuity. It is meant to inform, not forecast.
Additional Context
Record-keeping at scale becomes the foundation for analysis. Each outcome, whether typical or unusual, contributes to the stability and clarity of the long-run picture. 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
Across the long-horizon record, this entry adds one more entry to the long-horizon record. Reliability is a function of the growing record.