Bonus Match 5 Results
On Monday night, March 16, 2026, the Bonus Match 5 draw in Maryland brought 01 06 19 21 23 back after days away. Given an expected cadence of 1 in 575,757 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 16, 2026 in Maryland.
Draw times: Evening.
Our take on the Bonus Match 5 results
March 16, 2026Bonus Match 5 report — Monday night, March 16, 2026: 01 06 19 21 23 shows a notable pattern
On Monday night, March 16, 2026, the Bonus Match 5 draw in Maryland brought 01 06 19 21 23 back after days away. Given an expected cadence of 1 in 575,757 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 16, 2026, the Bonus Match 5 draw in Maryland brought 01 06 19 21 23 back after days away. Given an expected cadence of 1 in 575,757 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Combo Profile
As a number pattern, 01 06 19 21 23 uses 5 distinct numbers and a wide spread from 1 to 23.
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
To clarify: this analysis documents results recorded for Monday night, March 16, 2026 with benchmarking against long-run cadence. The goal is context, not prediction.
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. Context improves with scale. As more draws accumulate, isolated anomalies either normalize into baseline rates or reveal persistent deviations that warrant closer monitoring.
Adding to the Long-Term Record
Across the long-horizon record, this entry adds one more entry to the record. Reliability is a function of the growing record.