Tri-State Gimme 5 Results
On Monday night, February 2, 2026, the Tri-State Gimme 5 draw in New Hampshire produced a notable return: 03 04 06 25 33 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 2, 2026 in New Hampshire.
Draw times: Evening.
Our take on the Tri-State Gimme 5 results
February 2, 2026Tri-State Gimme 5 report — Monday night, February 2, 2026: 03 04 06 25 33 shows a notable pattern
On Monday night, February 2, 2026, the Tri-State Gimme 5 draw in New Hampshire produced a notable return: 03 04 06 25 33 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 Monday night, February 2, 2026, the Tri-State Gimme 5 draw in New Hampshire produced a notable return: 03 04 06 25 33 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
Beyond the drought, the numbers show a clean structure: 5 distinct numbers with no repeats, spanning 3 to 33 (wide spread).
Why Droughts Matter
Large gaps are descriptive, not directional - they record variance across time. They make variance visible across extended windows.
Data Notes
Specifically: this report documents results recorded for Monday night, February 2, 2026 and evaluates them against long-run frequency baselines. The intent is documentation, not forecasting.
From Stepzero
The takeaway: this reporting is shaped to keep a calm, evidence-first record as a reference point for continuity. The aim is context, not a call to action.
Additional Context
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.
Stability comes from the accumulation of entries. One draw alone does not define the pattern, but the record grows more reliable with each addition to the dataset.
Adding to the Long-Term Record
Across the long-term record, this appearance adds another archive entry to the record. Long-horizon stability comes from accumulation.