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Results + Analysis

Badger 5 Results

May 6, 2026Wisconsin

On Wednesday night, May 6, 2026, in the Wisconsin Badger 5 draw, 02 04 05 20 31 reappeared after a -day gap in the Wisconsin draw record. With an expected cadence of 1 in 169,911 draws, the gap sits well beyond typical spacing.

Winning numbers for 1 draw on May 6, 2026 in Wisconsin.

Draw times: Evening.

What's New Analysis

Our take on the Badger 5 results

May 6, 2026

Badger 5 report — Wednesday night, May 6, 2026: 02 04 05 20 31 shows a notable pattern

On Wednesday night, May 6, 2026, in the Wisconsin Badger 5 draw, 02 04 05 20 31 reappeared after a -day gap in the Wisconsin draw record. With an expected cadence of 1 in 169,911 draws, the gap sits well beyond typical spacing.

Overview

On Wednesday night, May 6, 2026, in the Wisconsin Badger 5 draw, 02 04 05 20 31 reappeared after a -day gap in the Wisconsin draw record. With an expected cadence of 1 in 169,911 draws, the gap sits well beyond typical spacing.

Combo Profile

As a number pattern, 02 04 05 20 31 uses 5 distinct numbers and a wide spread from 2 to 31.

Why Droughts Matter

Prolonged absences are descriptive, not forward-looking - they show where spacing departs from typical cadence. Their value is in long-horizon tracking.

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 produces these reports to provide a calm, evidence-first record of how draw patterns unfold over time. The aim is clarity and continuity - a reference point for long-horizon tracking rather than a call to action.

Additional Context

Context improves with scale. As more draws accumulate, isolated anomalies either normalize into baseline rates or reveal persistent deviations that warrant closer monitoring.

Long-horizon measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges.

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

In the broader record, this return adds one more entry by one more data point. Reliability is a function of the growing record.

1Recorded appearances

Draw Results

EveningMay 6, 2026
Results
2452031