Fantasy 5 Results
On Sunday night, May 31, 2026, the Fantasy 5 draw in Michigan produced a notable return: 10 17 19 24 35 after days of absence. Against an expected cadence of 1 in 575,757 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Winning numbers for 1 draw on May 31, 2026 in Michigan.
Draw times: Evening.
Our take on the Fantasy 5 results
May 31, 2026Fantasy 5 report — Sunday night, May 31, 2026: 10 17 19 24 35 shows a notable pattern
On Sunday night, May 31, 2026, the Fantasy 5 draw in Michigan produced a notable return: 10 17 19 24 35 after days of absence. Against an expected cadence of 1 in 575,757 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Overview
On Sunday night, May 31, 2026, the Fantasy 5 draw in Michigan produced a notable return: 10 17 19 24 35 after days of absence. Against an expected cadence of 1 in 575,757 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Combo Profile
As a number shape, the combination uses 5 distinct numbers with no repeats noted. The spread runs 10 to 35 (wide).
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
This analysis uses the draw results recorded for Sunday night, May 31, 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
Long-horizon measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges. 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.
Adding to the Long-Term Record
The return of 10 17 19 24 35 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.