Match 6 Results
On Wednesday night, January 7, 2026, the Match 6 draw in Pennsylvania brought 04 05 15 17 25 42 back after days away. Given an expected cadence of 1 in 13,983,816 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Winning numbers for 1 draw on January 7, 2026 in Pennsylvania.
Draw times: Evening.
Our take on the Match 6 results
January 7, 2026Match 6 report — Wednesday night, January 7, 2026: 04 05 15 17 25 42 shows a notable pattern
On Wednesday night, January 7, 2026, the Match 6 draw in Pennsylvania brought 04 05 15 17 25 42 back after days away. Given an expected cadence of 1 in 13,983,816 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Overview
On Wednesday night, January 7, 2026, the Match 6 draw in Pennsylvania brought 04 05 15 17 25 42 back after days away. Given an expected cadence of 1 in 13,983,816 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Combo Profile
In terms of number structure, 04 05 15 17 25 42 holds 6 distinct numbers with no repeats present. The numbers span 4 to 42, a wide spread.
Why Droughts Matter
Extended absences function as context, not a signal - they mark how variance accumulates over long samples. They clarify how far outcomes drift from baseline cadence.
Data Notes
This analysis uses the draw results recorded for Wednesday night, January 7, 2026 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
Importantly: this series is designed to document distribution behavior over time as a calm, evidence-first reference. It is meant to inform, not forecast.
Additional Context
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. 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
With its return, 04 05 15 17 25 42 contributes another meaningful data point to the historical dataset. Each draw - whether routine or statistically unusual - refines the long-term view of how large random systems behave over time.