Mega Millions Results
On Tuesday night, March 25, 2025, the Mega Millions draw in Wisconsin produced a notable return: 01 05 17 39 62 after days of absence. Against an expected cadence of 1 in 12,103,014 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Winning numbers for 1 draw on March 25, 2025 in Wisconsin.
Draw times: Evening.
Our take on the Mega Millions results
March 25, 2025Mega Millions report — Tuesday night, March 25, 2025: 01 05 17 39 62 shows a notable pattern
On Tuesday night, March 25, 2025, the Mega Millions draw in Wisconsin produced a notable return: 01 05 17 39 62 after days of absence. Against an expected cadence of 1 in 12,103,014 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Overview
On Tuesday night, March 25, 2025, the Mega Millions draw in Wisconsin produced a notable return: 01 05 17 39 62 after days of absence. Against an expected cadence of 1 in 12,103,014 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 1 to 62 (wide spread).
Why Droughts Matter
Prolonged absences remain descriptive, not forward-looking - they mark how variance accumulates over long samples. They help analysts track drift against expected cadence.
Data Notes
This report summarizes observed outcomes for Tuesday night, March 25, 2025 and interprets them within the long-run distribution record. It does not imply a forecast or recommendation.
From Stepzero
The takeaway: this series is designed to document distribution behavior over time as context for disciplined analysis. The goal is clarity and stability.
Additional Context
Distribution analysis depends on consistent documentation. Each draw updates the record, allowing analysts to test whether deviations persist, reverse, or revert to expected ranges.
Long-horizon measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges.
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.