Mega Millions Results
On Tuesday night, April 30, 2024, the Mega Millions draw in Massachusetts brought 10 18 27 37 61 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 April 30, 2024 in Massachusetts.
Draw times: Evening.
Our take on the Mega Millions results
April 30, 2024Mega Millions report — Tuesday night, April 30, 2024: 10 18 27 37 61 shows a notable pattern
On Tuesday night, April 30, 2024, the Mega Millions draw in Massachusetts brought 10 18 27 37 61 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, April 30, 2024, the Mega Millions draw in Massachusetts brought 10 18 27 37 61 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 10 18 27 37 61 cover a wide range (10 to 61) with no repeats.
Why Droughts Matter
Extended absences like this provide context, not direction. They show how randomness behaves across large samples and help analysts quantify how often the system deviates from its baseline cadence.
Data Notes
This analysis uses the draw results recorded for Tuesday night, April 30, 2024 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
Stepzero focuses on documenting distribution behavior over large samples. Each report is a snapshot of observed outcomes, designed to support disciplined, long-term analysis.
Additional Context
Record-keeping at scale becomes the foundation for analysis. Each outcome, whether typical or unusual, contributes to the stability and clarity of the long-run picture. 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, 10 18 27 37 61 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.