Mega Millions Results
On Tuesday night, December 31, 2024, the Mega Millions draw in Maryland marked a notable return: 13 22 27 29 35 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 December 31, 2024 in Maryland.
Draw times: Evening.
Our take on the Mega Millions results
December 31, 2024Mega Millions report — Tuesday night, December 31, 2024: 13 22 27 29 35 shows a notable pattern
On Tuesday night, December 31, 2024, the Mega Millions draw in Maryland marked a notable return: 13 22 27 29 35 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, December 31, 2024, the Mega Millions draw in Maryland marked a notable return: 13 22 27 29 35 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
From a number profile angle, the combination holds 5 distinct numbers with no repeats noted. The range sits at 13 to 35, a wide spread.
Why Droughts Matter
Extended gaps remain descriptive, not a cue - they highlight the tail behavior of the system. They provide a clean read on long-run variance.
Data Notes
This analysis uses the draw results recorded for Tuesday night, December 31, 2024 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
At Stepzero, the priority is accuracy and context. This report is intended as a historical record entry, not a forecast.
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. 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
With its return, 13 22 27 29 35 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.