Tri-State Gimme 5 Results
On Friday night, February 13, 2026, the Tri-State Gimme 5 draw in New Hampshire produced a notable return: 01 05 06 16 39 after days of absence. Against an expected cadence of 1 in 575,757 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Winning numbers for 1 draw on February 13, 2026 in New Hampshire.
Draw times: Evening.
Our take on the Tri-State Gimme 5 results
February 13, 2026Tri-State Gimme 5 report — Friday night, February 13, 2026: 01 05 06 16 39 shows a notable pattern
On Friday night, February 13, 2026, the Tri-State Gimme 5 draw in New Hampshire produced a notable return: 01 05 06 16 39 after days of absence. Against an expected cadence of 1 in 575,757 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Overview
On Friday night, February 13, 2026, the Tri-State Gimme 5 draw in New Hampshire produced a notable return: 01 05 06 16 39 after days of absence. Against an expected cadence of 1 in 575,757 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Combo Profile
In terms of number structure, 01 05 06 16 39 uses 5 distinct numbers and no repeats. The spread runs 1 to 39 (wide).
Why Droughts Matter
Deep gaps are context markers, not a signal - they show how distribution tails behave. They help quantify how often outcomes move into the tails.
Data Notes
This analysis uses the draw results recorded for Friday night, February 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
To be clear: this series is meant to document distribution behavior over time 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.
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.
Adding to the Long-Term Record
Over the long run, this entry adds another archive entry to the cumulative record. The record gains clarity as entries accumulate.