Mega Millions Results
On Friday night, September 5, 2025, the Mega Millions draw in West Virginia produced a notable return: 06 14 36 58 62 after days of absence. The length of the gap places this result beyond typical spacing, making it a meaningful entry for long-term distribution tracking.
Winning numbers for 1 draw on September 5, 2025 in West Virginia.
Draw times: Evening.
Our take on the Mega Millions results
September 5, 2025Mega Millions report — Friday night, September 5, 2025: 06 14 36 58 62 shows a notable pattern
On Friday night, September 5, 2025, the Mega Millions draw in West Virginia produced a notable return: 06 14 36 58 62 after days of absence. The length of the gap places this result beyond typical spacing, making it a meaningful entry for long-term distribution tracking.
Overview
On Friday night, September 5, 2025, the Mega Millions draw in West Virginia produced a notable return: 06 14 36 58 62 after days of absence. The length of the gap places this result beyond typical spacing, making it a meaningful entry for long-term distribution tracking.
Combo Profile
The numbers in 06 14 36 58 62 cover a wide range (6 to 62) with no repeats.
Why Droughts Matter
A long drought is descriptive rather than predictive. It records variance across time and helps analysts evaluate whether outcomes are tracking within expected frequency bands or drifting into the tails of the distribution.
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
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.
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
The return of 06 14 36 58 62 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.