Mega Millions Results
On Tuesday night, June 11, 2024, the Mega Millions draw in Maryland produced a notable return: 01 05 07 22 24 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 June 11, 2024 in Maryland.
Draw times: Evening.
Our take on the Mega Millions results
June 11, 2024Mega Millions report — Tuesday night, June 11, 2024: 01 05 07 22 24 shows a notable pattern
On Tuesday night, June 11, 2024, the Mega Millions draw in Maryland produced a notable return: 01 05 07 22 24 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, June 11, 2024, the Mega Millions draw in Maryland produced a notable return: 01 05 07 22 24 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
In terms of number structure, the pattern lands on 5 distinct numbers with no repeats in the pattern. The spread runs 1 to 24 (wide).
Why Droughts Matter
Long gaps are context, not a forecast - they highlight the tail behavior of the system. They help quantify how often outcomes move into the tails.
Data Notes
Results are evaluated against historical frequency baselines where available. The goal is documentation and context rather than prediction.
From Stepzero
At Stepzero, the priority is accuracy and context. This report is intended as a historical record entry, not a forecast.
Additional Context
Long-horizon measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges.
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.
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.
Adding to the Long-Term Record
Across the long-term record, this entry adds a fresh entry to the record to the cumulative record. The long-run picture sharpens as entries accrue.