Mega Millions Results
On Tuesday night, April 21, 2026, the Mega Millions draw in Illinois marked a notable return: 01 36 43 56 58 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 12,103,014 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Winning numbers for 1 draw on April 21, 2026 in Illinois.
Draw times: Evening.
Our take on the Mega Millions results
April 21, 2026Mega Millions report — Tuesday night, April 21, 2026: 01 36 43 56 58 shows a notable pattern
On Tuesday night, April 21, 2026, the Mega Millions draw in Illinois marked a notable return: 01 36 43 56 58 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 12,103,014 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Overview
On Tuesday night, April 21, 2026, the Mega Millions draw in Illinois marked a notable return: 01 36 43 56 58 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 12,103,014 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Combo Profile
Beyond the drought, the numbers show a clean structure: 5 distinct numbers with no repeats, spanning 1 to 58 (wide spread).
Why Droughts Matter
Large gaps are context markers, not forward-looking - they highlight the tail behavior of the system. They offer context for distribution stability over time.
Data Notes
This report summarizes observed outcomes for Tuesday night, April 21, 2026 and interprets them within the long-run distribution record. It does not imply a forecast or recommendation.
From Stepzero
Stepzero focuses on documenting distribution behavior over large samples. Each report is a snapshot of observed outcomes, designed to support disciplined, long-term analysis.
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 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
Over the broader record, this result contributes one more record entry by one more data point. Reliability is a function of the growing record.