Mega Millions Results
On Tuesday night, September 2, 2025, the Mega Millions draw in Vermont marked a notable return: 07 17 35 40 64 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 12,103,014 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Winning numbers for 1 draw on September 2, 2025 in Vermont.
Draw times: Evening.
Our take on the Mega Millions results
September 2, 2025Mega Millions report — Tuesday night, September 2, 2025: 07 17 35 40 64 shows a notable pattern
On Tuesday night, September 2, 2025, the Mega Millions draw in Vermont marked a notable return: 07 17 35 40 64 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 12,103,014 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Overview
On Tuesday night, September 2, 2025, the Mega Millions draw in Vermont marked a notable return: 07 17 35 40 64 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 12,103,014 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Combo Profile
Beyond the drought, the numbers show a clean structure: 5 distinct numbers with no repeats, spanning 7 to 64 (wide spread).
Why Droughts Matter
Deep gaps are context, not forward-looking - they show how distribution tails behave. They help quantify how often outcomes move into the tails.
Data Notes
Worth noting: this analysis documents the draw results for Tuesday night, September 2, 2025 with comparison to long-run frequency baselines. The focus is documentation over 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
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 07 17 35 40 64 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.