Treasure Hunt Results
On Monday midday, June 9, 2025, the Treasure Hunt draw in Pennsylvania produced a notable return: 11 13 22 25 29 after days of absence. Against an expected cadence of 1 in 142,506 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Winning numbers for 1 draw on June 9, 2025 in Pennsylvania.
Draw times: Day.
Our take on the Treasure Hunt results
June 9, 2025Treasure Hunt report — Monday midday, June 9, 2025: 11 13 22 25 29 shows a notable pattern
On Monday midday, June 9, 2025, the Treasure Hunt draw in Pennsylvania produced a notable return: 11 13 22 25 29 after days of absence. Against an expected cadence of 1 in 142,506 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Overview
On Monday midday, June 9, 2025, the Treasure Hunt draw in Pennsylvania produced a notable return: 11 13 22 25 29 after days of absence. Against an expected cadence of 1 in 142,506 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Combo Profile
As a number pattern, 11 13 22 25 29 uses 5 distinct numbers and a wide spread from 11 to 29.
Why Droughts Matter
Long gaps are context markers, not directional - they show how distribution tails behave. They help quantify how often outcomes move into the tails.
Data Notes
This analysis uses the draw results recorded for Monday midday, June 9, 2025 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
Importantly: these reports are intended to keep the long-horizon record steady for analysts and long-run tracking. The priority is accuracy and continuity.
Additional Context
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. 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
With its return, 11 13 22 25 29 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.