Cash 5 Results
On Wednesday night, May 13, 2026, the Cash 5 draw in Pennsylvania brought 07 09 15 20 21 back after days away. Given an expected cadence of 1 in 962,598 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 May 13, 2026 in Pennsylvania.
Draw times: Evening.
Our take on the Cash 5 results
May 13, 2026Cash 5 report — Wednesday night, May 13, 2026: 07 09 15 20 21 shows a notable pattern
On Wednesday night, May 13, 2026, the Cash 5 draw in Pennsylvania brought 07 09 15 20 21 back after days away. Given an expected cadence of 1 in 962,598 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Overview
On Wednesday night, May 13, 2026, the Cash 5 draw in Pennsylvania brought 07 09 15 20 21 back after days away. Given an expected cadence of 1 in 962,598 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Combo Profile
From a number-profile view, this sequence lands on 5 distinct numbers with no repeats. The spread runs 7 to 21 (wide).
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
Results are evaluated against historical frequency baselines where available. The goal is documentation and context rather than 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
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 measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges.
Distribution analysis depends on consistent documentation. Each draw updates the record, allowing analysts to test whether deviations persist, reverse, or revert to expected ranges.
Adding to the Long-Term Record
Across the long-term record, this result extends the historical ledger to the long-horizon record. It is the cumulative record that makes analysis stable.