Hit 5 Results
On Tuesday night, February 24, 2026, for Washington's Hit 5 draw, 04 26 30 31 42 showed up again following a -day absence for Washington. The gap is large relative to 1 in 850,668 draws, placing it deep in the tail.
Winning numbers for 1 draw on February 24, 2026 in Washington.
Draw times: Evening.
Our take on the Hit 5 results
February 24, 2026Hit 5 report — Tuesday night, February 24, 2026: 04 26 30 31 42 shows a notable pattern
On Tuesday night, February 24, 2026, for Washington's Hit 5 draw, 04 26 30 31 42 showed up again following a -day absence for Washington. The gap is large relative to 1 in 850,668 draws, placing it deep in the tail.
Overview
On Tuesday night, February 24, 2026, for Washington's Hit 5 draw, 04 26 30 31 42 showed up again following a -day absence for Washington. The gap is large relative to 1 in 850,668 draws, placing it deep in the tail.
Combo Profile
The numbers in 04 26 30 31 42 cover a wide range (4 to 42) with no repeats.
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
To clarify: this analysis summarizes the draw results for Tuesday night, February 24, 2026 and compares them to historical cadence. The goal is context, not prediction.
From Stepzero
Stepzero focuses on documenting distribution behavior over large samples. Each report is a snapshot of observed outcomes, designed to support disciplined, long-term analysis.
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.
Stability comes from the accumulation of entries. One draw alone does not define the pattern, but the record grows more reliable with each addition to the dataset.
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.