Match 6 Results
On Tuesday night, April 21, 2026, the Match 6 draw in Pennsylvania brought 05 12 15 42 46 49 back after days away. Given an expected cadence of 1 in 13,983,816 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Winning numbers for 1 draw on April 21, 2026 in Pennsylvania.
Draw times: Evening.
Our take on the Match 6 results
April 21, 2026Match 6 report — Tuesday night, April 21, 2026: 05 12 15 42 46 49 shows a notable pattern
On Tuesday night, April 21, 2026, the Match 6 draw in Pennsylvania brought 05 12 15 42 46 49 back after days away. Given an expected cadence of 1 in 13,983,816 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Overview
On Tuesday night, April 21, 2026, the Match 6 draw in Pennsylvania brought 05 12 15 42 46 49 back after days away. Given an expected cadence of 1 in 13,983,816 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Combo Profile
As a number pattern, 05 12 15 42 46 49 uses 6 distinct numbers and a wide spread from 5 to 49.
Why Droughts Matter
Extended absences are context markers, not forward-looking - they show how distribution tails behave. They make variance visible across extended windows.
Data Notes
This analysis uses the draw results recorded for Tuesday night, April 21, 2026 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
At Stepzero, the priority is accuracy and context. This report is intended as a historical record entry, not a forecast.
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 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 05 12 15 42 46 49 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.