Multi-Match Results
On Thursday night, March 12, 2026 in Maryland, 09 15 24 26 27 35 landed again after days away in the Maryland record. By the expected cadence of 1 in 6,096,454 draws, the interval is a long-gap event.
Winning numbers for 1 draw on March 12, 2026 in Maryland.
Draw times: Evening.
Our take on the Multi-Match results
March 12, 2026Multi-Match report — Thursday night, March 12, 2026: 09 15 24 26 27 35 shows a notable pattern
On Thursday night, March 12, 2026 in Maryland, 09 15 24 26 27 35 landed again after days away in the Maryland record. By the expected cadence of 1 in 6,096,454 draws, the interval is a long-gap event.
Overview
On Thursday night, March 12, 2026 in Maryland, 09 15 24 26 27 35 landed again after days away in the Maryland record. By the expected cadence of 1 in 6,096,454 draws, the interval is a long-gap event.
Combo Profile
As a number pattern, 09 15 24 26 27 35 uses 6 distinct numbers and a wide spread from 9 to 35.
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
This analysis uses the draw results recorded for Thursday night, March 12, 2026 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
At Stepzero, the priority is accuracy and context. This report is intended as a historical record entry, not a forecast.
Additional Context
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.
Context improves with scale. As more draws accumulate, isolated anomalies either normalize into baseline rates or reveal persistent deviations that warrant closer monitoring.
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
This result adds a measurable entry to the long-term record. Over time, those entries are what sharpen distribution analysis and reveal whether the system is tracking its expected cadence.