Tri-State Gimme 5 Results
On Monday night, June 24, 2024, the Tri-State Gimme 5 draw in New Hampshire marked a notable return: 17 27 31 32 36 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 June 24, 2024 in New Hampshire.
Draw times: Evening.
Our take on the Tri-State Gimme 5 results
June 24, 2024Tri-State Gimme 5 report — Monday night, June 24, 2024: 17 27 31 32 36 shows a notable pattern
On Monday night, June 24, 2024, the Tri-State Gimme 5 draw in New Hampshire marked a notable return: 17 27 31 32 36 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 Monday night, June 24, 2024, the Tri-State Gimme 5 draw in New Hampshire marked a notable return: 17 27 31 32 36 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
From a pattern view, the pattern lands on 5 distinct numbers and no repeats. The numbers cover 17 to 36 with a wide range.
Why Droughts Matter
Large gaps function as context, not a signal - they show where spacing departs from typical cadence. They make variance visible across extended windows.
Data Notes
This analysis uses the draw results recorded for Monday night, June 24, 2024 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
Stepzero focuses on documenting distribution behavior over large samples. Each report is a snapshot of observed outcomes, designed to support disciplined, long-term analysis.
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. 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
In long-horizon tracking, this entry adds another data point by one more data point. The long-run picture sharpens as entries accrue.