Match 6 Results
On Monday night, October 6, 2025, the Match 6 draw in Pennsylvania marked a notable return: 01 22 26 30 32 39 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 13,983,816 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Winning numbers for 1 draw on October 6, 2025 in Pennsylvania.
Draw times: Evening.
Our take on the Match 6 results
October 6, 2025Match 6 report — Monday night, October 6, 2025: 01 22 26 30 32 39 shows a notable pattern
On Monday night, October 6, 2025, the Match 6 draw in Pennsylvania marked a notable return: 01 22 26 30 32 39 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 13,983,816 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Overview
On Monday night, October 6, 2025, the Match 6 draw in Pennsylvania marked a notable return: 01 22 26 30 32 39 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 13,983,816 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Combo Profile
As a number pattern, 01 22 26 30 32 39 uses 6 distinct numbers and a wide spread from 1 to 39.
Why Droughts Matter
Long gaps are best treated as context, not forward-looking - they mark how variance accumulates over long samples. Their value is in long-horizon tracking.
Data Notes
This report summarizes observed outcomes for Monday night, October 6, 2025 and interprets them within the long-run distribution record. It does not imply a forecast or recommendation.
From Stepzero
Simply put: this reporting is shaped to keep the record consistent over time as a reference point for continuity. The priority is accuracy and continuity.
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.
Adding to the Long-Term Record
The return of 01 22 26 30 32 39 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.