Match 6 Results
On Tuesday night, June 24, 2025, the Match 6 draw in Pennsylvania marked a notable return: 12 14 23 36 40 46 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 June 24, 2025 in Pennsylvania.
Draw times: Evening.
Our take on the Match 6 results
June 24, 2025Match 6 report — Tuesday night, June 24, 2025: 12 14 23 36 40 46 shows a notable pattern
On Tuesday night, June 24, 2025, the Match 6 draw in Pennsylvania marked a notable return: 12 14 23 36 40 46 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 Tuesday night, June 24, 2025, the Match 6 draw in Pennsylvania marked a notable return: 12 14 23 36 40 46 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
The numbers in 12 14 23 36 40 46 cover a wide range (12 to 46) with no repeats.
Why Droughts Matter
Long droughts remain descriptive, not predictive - they mark how variance accumulates over long samples. They help quantify how often outcomes move into the tails.
Data Notes
This analysis uses the draw results recorded for Tuesday night, June 24, 2025 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
In summary: this reporting is designed to keep a calm, evidence-first record as a reference point for continuity. 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. 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
The return of 12 14 23 36 40 46 expands the archive by one more data point. It is the accumulation of these entries, not a single draw, that defines the reliability of long-horizon analysis.