Bonus Match 5 Results
On Sunday night, May 31, 2026, for Maryland's Bonus Match 5 draw, 14 16 18 26 29 came back after days away in Maryland. The gap is large relative to 1 in 575,757 draws, placing it deep in the tail.
Winning numbers for 1 draw on May 31, 2026 in Maryland.
Draw times: Evening.
Our take on the Bonus Match 5 results
May 31, 2026Bonus Match 5 report — Sunday night, May 31, 2026: 14 16 18 26 29 shows a notable pattern
On Sunday night, May 31, 2026, for Maryland's Bonus Match 5 draw, 14 16 18 26 29 came back after days away in Maryland. The gap is large relative to 1 in 575,757 draws, placing it deep in the tail.
Overview
On Sunday night, May 31, 2026, for Maryland's Bonus Match 5 draw, 14 16 18 26 29 came back after days away in Maryland. The gap is large relative to 1 in 575,757 draws, placing it deep in the tail.
Combo Profile
The numbers in 14 16 18 26 29 cover a wide range (14 to 29) with no repeats.
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 report summarizes observed outcomes for Sunday night, May 31, 2026 and interprets them within the long-run distribution record. It does not imply a forecast or recommendation.
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
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 measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges.
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.