Multi-Match Results
On Monday night, March 30, 2026, the Multi-Match draw in Maryland brought 01 03 05 16 20 28 back after days away. Given an expected cadence of 1 in 6,096,454 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 March 30, 2026 in Maryland.
Draw times: Evening.
Our take on the Multi-Match results
March 30, 2026Multi-Match report — Monday night, March 30, 2026: 01 03 05 16 20 28 shows a notable pattern
On Monday night, March 30, 2026, the Multi-Match draw in Maryland brought 01 03 05 16 20 28 back after days away. Given an expected cadence of 1 in 6,096,454 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Overview
On Monday night, March 30, 2026, the Multi-Match draw in Maryland brought 01 03 05 16 20 28 back after days away. Given an expected cadence of 1 in 6,096,454 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Combo Profile
Beyond the drought, the numbers show a clean structure: 6 distinct numbers with no repeats, spanning 1 to 28 (wide spread).
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 report summarizes observed outcomes for Monday night, March 30, 2026 and interprets them within the long-run distribution record. It does not imply a forecast or recommendation.
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 measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges. Stability comes from the accumulation of entries. One draw alone does not define the pattern, but the record grows more reliable with each addition to the dataset.
Adding to the Long-Term Record
With its return, 01 03 05 16 20 28 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.