Mega Millions Results
On Friday night, February 6, 2026, the Mega Millions draw in Vermont brought 13 21 25 52 62 back after days away. Given an expected cadence of 1 in 12,103,014 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Winning numbers for 1 draw on February 6, 2026 in Vermont.
Draw times: Evening.
Our take on the Mega Millions results
February 6, 2026Mega Millions report — Friday night, February 6, 2026: 13 21 25 52 62 shows a notable pattern
On Friday night, February 6, 2026, the Mega Millions draw in Vermont brought 13 21 25 52 62 back after days away. Given an expected cadence of 1 in 12,103,014 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Overview
On Friday night, February 6, 2026, the Mega Millions draw in Vermont brought 13 21 25 52 62 back after days away. Given an expected cadence of 1 in 12,103,014 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Combo Profile
As a number pattern, 13 21 25 52 62 uses 5 distinct numbers and a wide spread from 13 to 62.
Why Droughts Matter
Droughts do not indicate what will happen next - they simply document what has already occurred. Their value lies in measuring distribution over long horizons and identifying when a combination performs far above or below its expected appearance rate.
Data Notes
Results are evaluated against historical frequency baselines where available. The goal is documentation and context rather than prediction.
From Stepzero
Stepzero produces these reports to provide a calm, evidence-first record of how draw patterns unfold over time. The aim is clarity and continuity - a reference point for long-horizon tracking rather than a call to action.
Additional Context
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. Long-horizon measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges.
Adding to the Long-Term Record
The return of 13 21 25 52 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.