Tri-State Gimme 5 Results
On Friday night, March 20, 2026, 13 14 28 31 35 reappeared following a -day absence in New Hampshire. With an expected cadence of 1 in 575,757 draws, the gap sits well beyond typical spacing.
Winning numbers for 1 draw on March 20, 2026 in New Hampshire.
Draw times: Evening.
Our take on the Tri-State Gimme 5 results
March 20, 2026Tri-State Gimme 5 report — Friday night, March 20, 2026: 13 14 28 31 35 shows a notable pattern
On Friday night, March 20, 2026, 13 14 28 31 35 reappeared following a -day absence in New Hampshire. With an expected cadence of 1 in 575,757 draws, the gap sits well beyond typical spacing.
Overview
On Friday night, March 20, 2026, 13 14 28 31 35 reappeared following a -day absence in New Hampshire. With an expected cadence of 1 in 575,757 draws, the gap sits well beyond typical spacing.
Combo Profile
In structural terms, this result settles on 5 distinct numbers and no repeats. The numbers span 13 to 35, a wide spread.
Why Droughts Matter
Extended absences like this provide context, not direction. They show how randomness behaves across large samples and help analysts quantify how often the system deviates from its baseline cadence.
Data Notes
This analysis uses the draw results recorded for Friday night, March 20, 2026 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
In summary: this reporting is shaped to keep the record consistent over time for analysts and long-run tracking. The intent is clarity, not prediction.
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 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
This result adds a measurable entry to the long-term record. Over time, those entries are what sharpen distribution analysis and reveal whether the system is tracking its expected cadence.