Mega Millions Results
On Tuesday night, May 6, 2025, the Mega Millions draw in Vermont brought 16 17 43 46 58 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 May 6, 2025 in Vermont.
Draw times: Evening.
Our take on the Mega Millions results
May 6, 2025Mega Millions report — Tuesday night, May 6, 2025: 16 17 43 46 58 shows a notable pattern
On Tuesday night, May 6, 2025, the Mega Millions draw in Vermont brought 16 17 43 46 58 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 Tuesday night, May 6, 2025, the Mega Millions draw in Vermont brought 16 17 43 46 58 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
The numbers in 16 17 43 46 58 cover a wide range (16 to 58) with no repeats.
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
This analysis uses the draw results recorded for Tuesday night, May 6, 2025 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
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
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 16 17 43 46 58 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.