Multi-Match Results
On Monday night, January 13, 2025, the Multi-Match draw in Maryland produced a notable return: 09 16 20 35 37 43 after days of absence. Against an expected cadence of 1 in 6,096,454 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Winning numbers for 1 draw on January 13, 2025 in Maryland.
Draw times: Evening.
Our take on the Multi-Match results
January 13, 2025Multi-Match report — Monday night, January 13, 2025: 09 16 20 35 37 43 shows a notable pattern
On Monday night, January 13, 2025, the Multi-Match draw in Maryland produced a notable return: 09 16 20 35 37 43 after days of absence. Against an expected cadence of 1 in 6,096,454 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Overview
On Monday night, January 13, 2025, the Multi-Match draw in Maryland produced a notable return: 09 16 20 35 37 43 after days of absence. Against an expected cadence of 1 in 6,096,454 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Combo Profile
From a number-profile view, this draw lands on 6 distinct numbers and no repeats. The numbers span 9 to 43, a wide spread.
Why Droughts Matter
Extended absences like this provide context, not direction. They show how randomness behaves across large samples and help analysts quantify how often the system deviates from its baseline cadence.
Data Notes
This analysis uses the draw results recorded for Monday night, January 13, 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 series is designed to keep the record consistent over time as context for disciplined analysis. The aim is a trustworthy record.
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. Record-keeping at scale becomes the foundation for analysis. Each outcome, whether typical or unusual, contributes to the stability and clarity of the long-run picture.
Adding to the Long-Term Record
With its return, 09 16 20 35 37 43 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.