All or Nothing Results
On Saturday midday, May 23, 2026, the All or Nothing draw in Wisconsin marked a notable return: 01 03 04 06 08 12 13 16 17 19 20 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 705,432 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Winning numbers for 2 draws on May 23, 2026 in Wisconsin.
Draw times: D, Evening.
Our take on the All or Nothing results
May 23, 2026All or Nothing report — Saturday midday, May 23, 2026: 01 03 04 06 08 12 13 16 17 19 20 shows a notable pattern
On Saturday midday, May 23, 2026, the All or Nothing draw in Wisconsin marked a notable return: 01 03 04 06 08 12 13 16 17 19 20 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 705,432 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Overview
On Saturday midday, May 23, 2026, the All or Nothing draw in Wisconsin marked a notable return: 01 03 04 06 08 12 13 16 17 19 20 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 705,432 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Combo Profile
As a number pattern, 01 03 04 06 08 12 13 16 17 19 20 uses 11 distinct numbers and a wide spread from 1 to 20.
Why Droughts Matter
Long gaps are context markers, not predictive - they track where outcomes drift from baseline spacing. They offer context for distribution stability over time.
Data Notes
This report summarizes observed outcomes for Saturday midday, May 23, 2026 and interprets them within the long-run distribution record. It does not imply a forecast or recommendation.
From Stepzero
In summary: this reporting is shaped to keep the long-horizon record steady for analysts and long-run tracking. The focus is long-horizon context.
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.
Adding to the Long-Term Record
With its return, 01 03 04 06 08 12 13 16 17 19 20 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.