Mega Millions Results
On Friday night, May 1, 2026, the Mega Millions draw in Washington marked a notable return: 16 21 27 41 61 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 May 1, 2026 in Washington.
Draw times: Evening.
Our take on the Mega Millions results
May 1, 2026Mega Millions report — Friday night, May 1, 2026: 16 21 27 41 61 shows a notable pattern
On Friday night, May 1, 2026, the Mega Millions draw in Washington marked a notable return: 16 21 27 41 61 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 Friday night, May 1, 2026, the Mega Millions draw in Washington marked a notable return: 16 21 27 41 61 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
The numbers in 16 21 27 41 61 cover a wide range (16 to 61) with no repeats.
Why Droughts Matter
Extended absences are descriptive, not directional - they show where spacing departs from typical cadence. They make variance visible across extended windows.
Data Notes
This report summarizes observed outcomes for Friday night, May 1, 2026 and interprets them within the long-run distribution record. It does not imply a forecast or recommendation.
From Stepzero
At Stepzero, the priority is accuracy and context. This report is intended as a historical record entry, not a forecast.
Additional Context
Record-keeping at scale becomes the foundation for analysis. Each outcome, whether typical or unusual, contributes to the stability and clarity of the long-run picture.
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.
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.