Match 6 Results
On Monday night, September 29, 2025, the Match 6 draw in Pennsylvania produced a notable return: 01 10 19 20 27 32 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 29, 2025 in Pennsylvania.
Draw times: Evening.
Our take on the Match 6 results
September 29, 2025Match 6 report — Monday night, September 29, 2025: 01 10 19 20 27 32 shows a notable pattern
On Monday night, September 29, 2025, the Match 6 draw in Pennsylvania produced a notable return: 01 10 19 20 27 32 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 Monday night, September 29, 2025, the Match 6 draw in Pennsylvania produced a notable return: 01 10 19 20 27 32 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 10 19 20 27 32 uses 6 distinct numbers and a wide spread from 1 to 32.
Why Droughts Matter
Extended absences are best treated as context, not a cue - they show how distribution tails behave. They offer context for distribution stability over time.
Data Notes
To clarify: this report documents results recorded for Monday night, September 29, 2025 and benchmarks them against historical frequency baselines. The focus is documentation over prediction.
From Stepzero
To be clear: this reporting is built to keep the record consistent over time as context for disciplined analysis. The aim is a trustworthy record.
Additional Context
Long-horizon measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges.
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 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 return adds a new point to the dataset by one more data point. It is the cumulative record that makes analysis stable.