Match 6 Results
On Friday night, September 26, 2025, the Match 6 draw in Pennsylvania produced a notable return: 01 09 13 31 34 39 after days of absence. Against an expected cadence of 1 in 13,983,816 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Winning numbers for 1 draw on September 26, 2025 in Pennsylvania.
Draw times: Evening.
Our take on the Match 6 results
September 26, 2025Match 6 report — Friday night, September 26, 2025: 01 09 13 31 34 39 shows a notable pattern
On Friday night, September 26, 2025, the Match 6 draw in Pennsylvania produced a notable return: 01 09 13 31 34 39 after days of absence. Against an expected cadence of 1 in 13,983,816 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Overview
On Friday night, September 26, 2025, the Match 6 draw in Pennsylvania produced a notable return: 01 09 13 31 34 39 after days of absence. Against an expected cadence of 1 in 13,983,816 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Combo Profile
As a number pattern, 01 09 13 31 34 39 uses 6 distinct numbers and a wide spread from 1 to 39.
Why Droughts Matter
Deep gaps remain descriptive, not a forecast - they mark how variance accumulates over long samples. They clarify how far outcomes drift from baseline cadence.
Data Notes
To clarify: this analysis records outcomes logged on Friday night, September 26, 2025 and benchmarks them against historical frequency baselines. This is descriptive, not predictive.
From Stepzero
At Stepzero, the priority is accuracy and context. This report is intended as a historical record entry, not a forecast.
Additional Context
Record-keeping at scale becomes the foundation for analysis. Each outcome, whether typical or unusual, contributes to the stability and clarity of the long-run picture.
Distribution analysis depends on consistent documentation. Each draw updates the record, allowing analysts to test whether deviations persist, reverse, or revert to 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
From a long-horizon view, this appearance extends the historical ledger to the long-run dataset. Stability comes from the growing record, not any one draw.