Mega Millions Results
On Tuesday night, April 21, 2026, the Mega Millions draw in Pennsylvania produced a notable return: 01 36 43 56 58 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 April 21, 2026 in Pennsylvania.
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 Pennsylvania produced a notable return: 01 36 43 56 58 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, April 21, 2026, the Mega Millions draw in Pennsylvania produced a notable return: 01 36 43 56 58 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
As a number pattern, 01 36 43 56 58 uses 5 distinct numbers and a wide spread from 1 to 58.
Why Droughts Matter
Large gaps are context markers, not forward-looking - they record variance across time. They offer context for distribution stability over time.
Data Notes
This analysis uses the draw results recorded for Tuesday night, April 21, 2026 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
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
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. 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
In long-horizon tracking, this draw adds one more entry to the long-horizon record. Stability comes from the growing record, not any one draw.