Multi-Match Results
On Thursday night, April 2, 2026, the Multi-Match draw in Maryland produced a notable return: 07 16 22 24 40 43 after days of absence. Against an expected cadence of 1 in 6,096,454 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Winning numbers for 1 draw on April 2, 2026 in Maryland.
Draw times: Evening.
Our take on the Multi-Match results
April 2, 2026Multi-Match report — Thursday night, April 2, 2026: 07 16 22 24 40 43 shows a notable pattern
On Thursday night, April 2, 2026, the Multi-Match draw in Maryland produced a notable return: 07 16 22 24 40 43 after days of absence. Against an expected cadence of 1 in 6,096,454 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Overview
On Thursday night, April 2, 2026, the Multi-Match draw in Maryland produced a notable return: 07 16 22 24 40 43 after days of absence. Against an expected cadence of 1 in 6,096,454 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Combo Profile
As a number pattern, 07 16 22 24 40 43 uses 6 distinct numbers and a wide spread from 7 to 43.
Why Droughts Matter
A long drought is descriptive rather than predictive. It records variance across time and helps analysts evaluate whether outcomes are tracking within expected frequency bands or drifting into the tails of the distribution.
Data Notes
As documented: this analysis documents observed outcomes for Thursday night, April 2, 2026 with benchmarking against long-run cadence. This is documentation, not a forecast.
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 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. 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.
Adding to the Long-Term Record
With its return, 07 16 22 24 40 43 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.