Mega Millions Results
On Tuesday night, May 6, 2025, the Mega Millions draw in Connecticut marked a notable return: 16 17 43 46 58 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 May 6, 2025 in Connecticut.
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 Connecticut marked a notable return: 16 17 43 46 58 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, May 6, 2025, the Mega Millions draw in Connecticut marked a notable return: 16 17 43 46 58 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
As a number pattern, 16 17 43 46 58 uses 5 distinct numbers and a wide spread from 16 to 58.
Why Droughts Matter
Extended absences are best read as context, not predictive - they track where outcomes drift from baseline spacing. They make variance visible across extended windows.
Data Notes
To clarify: this report summarizes the recorded draws for Tuesday night, May 6, 2025 and benchmarks them against historical frequency baselines. It is intended for context, not forecasting.
From Stepzero
At its core: this series is meant to preserve a stable long-horizon record as a reference point for continuity. The aim is a trustworthy record.
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. Distribution analysis depends on consistent documentation. Each draw updates the record, allowing analysts to test whether deviations persist, reverse, or revert to expected ranges.
Adding to the Long-Term Record
With its return, 16 17 43 46 58 contributes another meaningful data point to the historical dataset. Each draw - whether routine or statistically unusual - refines the long-term view of how large random systems behave over time.