Match 6 Results
On Sunday night, October 26, 2025, the Match 6 draw in Pennsylvania marked a notable return: 02 17 26 34 35 43 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 26, 2025 in Pennsylvania.
Draw times: Evening.
Our take on the Match 6 results
October 26, 2025Match 6 report — Sunday night, October 26, 2025: 02 17 26 34 35 43 shows a notable pattern
On Sunday night, October 26, 2025, the Match 6 draw in Pennsylvania marked a notable return: 02 17 26 34 35 43 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 Sunday night, October 26, 2025, the Match 6 draw in Pennsylvania marked a notable return: 02 17 26 34 35 43 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, 02 17 26 34 35 43 uses 6 distinct numbers and a wide spread from 2 to 43.
Why Droughts Matter
Deep gaps are best read as context, not predictive - they show how distribution tails behave. Their value is in long-horizon tracking.
Data Notes
The method: this report documents outcomes documented for Sunday night, October 26, 2025 and benchmarks them against historical frequency baselines. The focus is documentation over prediction.
From Stepzero
The core idea: this reporting is shaped to keep a calm, evidence-first record as a record, not a recommendation. The goal is clarity and stability.
Additional Context
Distribution analysis depends on consistent documentation. Each draw updates the record, allowing analysts to test whether deviations persist, reverse, or revert to expected ranges.
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
In the broader record, this result adds a fresh entry to the record by one more data point. Reliability is a function of the growing record.