Tri-State Megabucks Results
On Monday night, June 1, 2026, the Tri-State Megabucks draw in New Hampshire produced a notable return: 14 28 31 38 40 after days of absence. Against an expected cadence of 1 in 749,398 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Winning numbers for 1 draw on June 1, 2026 in New Hampshire.
Draw times: Evening.
Our take on the Tri-State Megabucks results
June 1, 2026Tri-State Megabucks report — Monday night, June 1, 2026: 14 28 31 38 40 shows a notable pattern
On Monday night, June 1, 2026, the Tri-State Megabucks draw in New Hampshire produced a notable return: 14 28 31 38 40 after days of absence. Against an expected cadence of 1 in 749,398 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Overview
On Monday night, June 1, 2026, the Tri-State Megabucks draw in New Hampshire produced a notable return: 14 28 31 38 40 after days of absence. Against an expected cadence of 1 in 749,398 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 14 to 40 (wide spread).
Why Droughts Matter
Prolonged absences are best treated as context, not forward-looking - they record variance across time. They provide a clean read on long-run variance.
Data Notes
This analysis uses the draw results recorded for Monday night, June 1, 2026 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
At Stepzero, the priority is accuracy and context. This report is intended as a historical record entry, not a forecast.
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. 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.