Bonus Match 5 Results
On Wednesday night, May 20, 2026, the Bonus Match 5 draw in Maryland marked a notable return: 04 09 14 30 35 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 575,757 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Winning numbers for 1 draw on May 20, 2026 in Maryland.
Draw times: Evening.
Our take on the Bonus Match 5 results
May 20, 2026Bonus Match 5 report — Wednesday night, May 20, 2026: 04 09 14 30 35 shows a notable pattern
On Wednesday night, May 20, 2026, the Bonus Match 5 draw in Maryland marked a notable return: 04 09 14 30 35 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 575,757 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Overview
On Wednesday night, May 20, 2026, the Bonus Match 5 draw in Maryland marked a notable return: 04 09 14 30 35 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 575,757 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Combo Profile
Beyond the drought, the numbers show a clean structure: 5 distinct numbers with no repeats, spanning 4 to 35 (wide spread).
Why Droughts Matter
Droughts do not indicate what will happen next - they simply document what has already occurred. Their value lies in measuring distribution over long horizons and identifying when a combination performs far above or below its expected appearance rate.
Data Notes
This analysis uses the draw results recorded for Wednesday night, May 20, 2026 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
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 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.