Mega Millions Results
On Tuesday night, January 6, 2026, the Mega Millions draw in Maryland produced a notable return: 09 39 47 58 68 after days of absence. Against an expected cadence of 1 in 12,103,014 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Winning numbers for 1 draw on January 6, 2026 in Maryland.
Draw times: Evening.
Our take on the Mega Millions results
January 6, 2026Mega Millions report — Tuesday night, January 6, 2026: 09 39 47 58 68 shows a notable pattern
On Tuesday night, January 6, 2026, the Mega Millions draw in Maryland produced a notable return: 09 39 47 58 68 after days of absence. Against an expected cadence of 1 in 12,103,014 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Overview
On Tuesday night, January 6, 2026, the Mega Millions draw in Maryland produced a notable return: 09 39 47 58 68 after days of absence. Against an expected cadence of 1 in 12,103,014 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Combo Profile
The numbers in 09 39 47 58 68 cover a wide range (9 to 68) with no repeats.
Why Droughts Matter
Large gaps are context markers, not a forecast - they show where spacing departs from typical cadence. They help quantify how often outcomes move into the tails.
Data Notes
This analysis uses the draw results recorded for Tuesday night, January 6, 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 reporting is designed to maintain continuity across the record as a record, not a recommendation. 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.
Long-horizon measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges.
Distribution analysis depends on consistent documentation. Each draw updates the record, allowing analysts to test whether deviations persist, reverse, or revert to expected ranges.
Adding to the Long-Term Record
This result adds a measurable entry to the long-term record. Over time, those entries are what sharpen distribution analysis and reveal whether the system is tracking its expected cadence.