Tri-State Gimme 5 Results
On Thursday night, May 28, 2026, the Tri-State Gimme 5 draw in New Hampshire brought 01 03 12 24 26 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 May 28, 2026 in New Hampshire.
Draw times: Evening.
Our take on the Tri-State Gimme 5 results
May 28, 2026Tri-State Gimme 5 report — Thursday night, May 28, 2026: 01 03 12 24 26 shows a notable pattern
On Thursday night, May 28, 2026, the Tri-State Gimme 5 draw in New Hampshire brought 01 03 12 24 26 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 Thursday night, May 28, 2026, the Tri-State Gimme 5 draw in New Hampshire brought 01 03 12 24 26 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
Beyond the drought, the numbers show a clean structure: 5 distinct numbers with no repeats, spanning 1 to 26 (wide spread).
Why Droughts Matter
Prolonged absences are best read as context, not directional - they highlight the tail behavior of the system. Their value is in long-horizon tracking.
Data Notes
In detail: this analysis summarizes outcomes documented for Thursday night, May 28, 2026 and anchors them against historical cadence. It is context-focused, not predictive.
From Stepzero
The takeaway: these reports are built to maintain continuity across the record as a calm, evidence-first reference. The goal is clarity and stability.
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. 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
The return of 01 03 12 24 26 expands the archive by one more data point. It is the accumulation of these entries, not a single draw, that defines the reliability of long-horizon analysis.