Tri-State Gimme 5 Results
On Tuesday night, June 4, 2024, the Tri-State Gimme 5 draw in New Hampshire brought 06 15 17 22 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 June 4, 2024 in New Hampshire.
Draw times: Evening.
Our take on the Tri-State Gimme 5 results
June 4, 2024Tri-State Gimme 5 report — Tuesday night, June 4, 2024: 06 15 17 22 28 shows a notable pattern
On Tuesday night, June 4, 2024, the Tri-State Gimme 5 draw in New Hampshire brought 06 15 17 22 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 Tuesday night, June 4, 2024, the Tri-State Gimme 5 draw in New Hampshire brought 06 15 17 22 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
The numbers in 06 15 17 22 28 cover a wide range (6 to 28) with no repeats.
Why Droughts Matter
Extended gaps are context, not a cue - they highlight the tail behavior of the system. Their value is in long-horizon tracking.
Data Notes
Results are evaluated against historical frequency baselines where available. The goal is documentation and context rather than prediction.
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
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.
Context improves with scale. As more draws accumulate, isolated anomalies either normalize into baseline rates or reveal persistent deviations that warrant closer monitoring.
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
With its return, 06 15 17 22 28 contributes another meaningful data point to the historical dataset. Each draw - whether routine or statistically unusual - refines the long-term view of how large random systems behave over time.