Fantasy 5 Results
On Wednesday night, April 22, 2026, the Fantasy 5 draw in Arizona marked a notable return: 01 02 17 25 34 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 749,398 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Winning numbers for 1 draw on April 22, 2026 in Arizona.
Draw times: Evening.
Our take on the Fantasy 5 results
April 22, 2026Fantasy 5 report — Wednesday night, April 22, 2026: 01 02 17 25 34 shows a notable pattern
On Wednesday night, April 22, 2026, the Fantasy 5 draw in Arizona marked a notable return: 01 02 17 25 34 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 749,398 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Overview
On Wednesday night, April 22, 2026, the Fantasy 5 draw in Arizona marked a notable return: 01 02 17 25 34 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 749,398 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 34 (wide spread).
Why Droughts Matter
Droughts do not indicate what will happen next - they simply document what has already occurred. Their value lies in measuring distribution over long horizons and identifying when a combination performs far above or below its expected appearance rate.
Data Notes
Worth noting: this report summarizes the draw results for Wednesday night, April 22, 2026 and evaluates them against long-run frequency baselines. The goal is context, not prediction.
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
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
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.