Fantasy 5 Results
On Wednesday night, May 6, 2026, the Fantasy 5 draw in Arizona produced a notable return: 01 14 23 37 41 after days of absence. Against an expected cadence of 1 in 749,398 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Winning numbers for 1 draw on May 6, 2026 in Arizona.
Draw times: Evening.
Our take on the Fantasy 5 results
May 6, 2026Fantasy 5 report — Wednesday night, May 6, 2026: 01 14 23 37 41 shows a notable pattern
On Wednesday night, May 6, 2026, the Fantasy 5 draw in Arizona produced a notable return: 01 14 23 37 41 after days of absence. Against an expected cadence of 1 in 749,398 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Overview
On Wednesday night, May 6, 2026, the Fantasy 5 draw in Arizona produced a notable return: 01 14 23 37 41 after days of absence. Against an expected cadence of 1 in 749,398 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Combo Profile
As a number pattern, 01 14 23 37 41 uses 5 distinct numbers and a wide spread from 1 to 41.
Why Droughts Matter
Extended absences like this provide context, not direction. They show how randomness behaves across large samples and help analysts quantify how often the system deviates from its baseline cadence.
Data Notes
This analysis uses the draw results recorded for Wednesday night, May 6, 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
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. 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
The return of 01 14 23 37 41 expands the archive by one more data point. It is the accumulation of these entries, not a single draw, that defines the reliability of long-horizon analysis.