Multi-Match Results
On Thursday night, May 1, 2025, the Multi-Match draw in Maryland brought 04 07 19 21 22 36 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 May 1, 2025 in Maryland.
Draw times: Evening.
Our take on the Multi-Match results
May 1, 2025Multi-Match report — Thursday night, May 1, 2025: 04 07 19 21 22 36 shows a notable pattern
On Thursday night, May 1, 2025, the Multi-Match draw in Maryland brought 04 07 19 21 22 36 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 Thursday night, May 1, 2025, the Multi-Match draw in Maryland brought 04 07 19 21 22 36 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 4 to 36 (wide spread).
Why Droughts Matter
Prolonged absences are context markers, not forward-looking - they track where outcomes drift from baseline spacing. They make variance visible across extended windows.
Data Notes
This analysis uses the draw results recorded for Thursday night, May 1, 2025 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
The takeaway: these reports are intended to maintain continuity across the record as a calm, evidence-first reference. The focus is long-horizon context.
Additional Context
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, 04 07 19 21 22 36 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.