Multi-Match Results
On Monday night, May 11, 2026, the Multi-Match draw in Maryland brought 09 12 15 20 22 31 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 11, 2026 in Maryland.
Draw times: Evening.
Our take on the Multi-Match results
May 11, 2026Multi-Match report — Monday night, May 11, 2026: 09 12 15 20 22 31 shows a notable pattern
On Monday night, May 11, 2026, the Multi-Match draw in Maryland brought 09 12 15 20 22 31 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, May 11, 2026, the Multi-Match draw in Maryland brought 09 12 15 20 22 31 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
Structurally, 09 12 15 20 22 31 lands on 6 distinct numbers and no repeats. The range sits at 9 to 31, a wide spread.
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
In detail: this analysis records observed outcomes for Monday night, May 11, 2026 and evaluates them against long-run frequency baselines. The focus is documentation over prediction.
From Stepzero
At Stepzero, the priority is accuracy and context. This report is intended as a historical record entry, not a forecast.
Additional Context
Distribution analysis depends on consistent documentation. Each draw updates the record, allowing analysts to test whether deviations persist, reverse, or revert to 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
The return of 09 12 15 20 22 31 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.