DC 4 Results
On Wednesday night, May 13, 2026, during the DC 4 draw in District of Columbia, 3707 showed up after days away in District of Columbia. Relative to 1 in 10,000 draws (~3,333 days), the gap reads as a long-horizon outlier.
Winning numbers for 3 draws on May 13, 2026 in District of Columbia.
Draw times: D, Evening, N.
Our take on the DC 4 results
May 13, 2026DC 4 report — Wednesday night, May 13, 2026: 3707 shows a notable pattern
On Wednesday night, May 13, 2026, during the DC 4 draw in District of Columbia, 3707 showed up after days away in District of Columbia. Relative to 1 in 10,000 draws (~3,333 days), the gap reads as a long-horizon outlier.
Overview
On Wednesday night, May 13, 2026, during the DC 4 draw in District of Columbia, 3707 showed up after days away in District of Columbia. Relative to 1 in 10,000 draws (~3,333 days), the gap reads as a long-horizon outlier.
Combo Profile
Beyond the drought, the digits show a clean structure: 3 distinct digits with a repeated digit, spanning 0 to 7 (wide spread).
Why Droughts Matter
Extended gaps are context markers, not directional - they document what has already happened. They help analysts track drift against expected cadence.
Data Notes
As documented: this report captures outcomes documented for Wednesday night, May 13, 2026 with reference to historical frequency baselines. It is context-focused, not predictive.
From Stepzero
At Stepzero, the priority is accuracy and context. This report is intended as a historical record entry, not a forecast.
Additional Context
Record-keeping at scale becomes the foundation for analysis. Each outcome, whether typical or unusual, contributes to the stability and clarity of the long-run picture. Long-horizon measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges. Long-horizon measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges. 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
Across the long-horizon record, this result adds another data point to the long-horizon record. Reliability is a function of the growing record.