Mega Millions Results
On Tuesday night, February 18, 2025, the Mega Millions draw in Wisconsin brought 01 20 25 58 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 February 18, 2025 in Wisconsin.
Draw times: Evening.
Our take on the Mega Millions results
February 18, 2025Mega Millions report — Tuesday night, February 18, 2025: 01 20 25 58 61 shows a notable pattern
On Tuesday night, February 18, 2025, the Mega Millions draw in Wisconsin brought 01 20 25 58 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, February 18, 2025, the Mega Millions draw in Wisconsin brought 01 20 25 58 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
As a number pattern, 01 20 25 58 61 uses 5 distinct numbers and a wide spread from 1 to 61.
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, February 18, 2025 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
Importantly: this series is designed to keep a calm, evidence-first 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
The return of 01 20 25 58 61 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.