Match 6 Results
On Monday night, January 5, 2026, the Match 6 draw in Pennsylvania produced a notable return: 03 07 08 13 17 49 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 January 5, 2026 in Pennsylvania.
Draw times: Evening.
Our take on the Match 6 results
January 5, 2026Match 6 report — Monday night, January 5, 2026: 03 07 08 13 17 49 shows a notable pattern
On Monday night, January 5, 2026, the Match 6 draw in Pennsylvania produced a notable return: 03 07 08 13 17 49 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, January 5, 2026, the Match 6 draw in Pennsylvania produced a notable return: 03 07 08 13 17 49 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, 03 07 08 13 17 49 uses 6 distinct numbers and a wide spread from 3 to 49.
Why Droughts Matter
Large gaps are best treated as context, not a forecast - they show where spacing departs from typical cadence. They make variance visible across extended windows.
Data Notes
This report summarizes observed outcomes for Monday night, January 5, 2026 and interprets them within the long-run distribution record. It does not imply a forecast or recommendation.
From Stepzero
Importantly: this reporting is shaped to preserve a stable long-horizon record as context for disciplined analysis. It is meant to inform, not forecast.
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.
Stability comes from the accumulation of entries. One draw alone does not define the pattern, but the record grows more reliable with each addition to the dataset.
Context improves with scale. As more draws accumulate, isolated anomalies either normalize into baseline rates or reveal persistent deviations that warrant closer monitoring.
Adding to the Long-Term Record
In long-horizon tracking, this return contributes one more record entry to the historical dataset. The long-run picture sharpens as entries accrue.