Mega Millions Results
On Tuesday night, November 25, 2025, the Mega Millions draw in West Virginia produced a notable return: 11 15 31 32 59 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 November 25, 2025 in West Virginia.
Draw times: Evening.
Our take on the Mega Millions results
November 25, 2025Mega Millions report — Tuesday night, November 25, 2025: 11 15 31 32 59 shows a notable pattern
On Tuesday night, November 25, 2025, the Mega Millions draw in West Virginia produced a notable return: 11 15 31 32 59 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, November 25, 2025, the Mega Millions draw in West Virginia produced a notable return: 11 15 31 32 59 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 11 to 59 (wide spread).
Why Droughts Matter
Extended absences are context markers, not a signal - they document what has already happened. They help quantify how often outcomes move into the tails.
Data Notes
This report summarizes observed outcomes for Tuesday night, November 25, 2025 and interprets them within the long-run distribution record. It does not imply a forecast or recommendation.
From Stepzero
Stepzero produces these reports to provide a calm, evidence-first record of how draw patterns unfold over time. The aim is clarity and continuity - a reference point for long-horizon tracking rather than a call to action.
Additional Context
Long-horizon measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges. 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, 11 15 31 32 59 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.