Tri-State Gimme 5 Results
On Wednesday night, May 6, 2026, the Tri-State Gimme 5 draw in Vermont marked a notable return: 03 13 24 31 39 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 6, 2026 in Vermont.
Draw times: Evening.
Our take on the Tri-State Gimme 5 results
May 6, 2026Tri-State Gimme 5 report — Wednesday night, May 6, 2026: 03 13 24 31 39 shows a notable pattern
On Wednesday night, May 6, 2026, the Tri-State Gimme 5 draw in Vermont marked a notable return: 03 13 24 31 39 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 6, 2026, the Tri-State Gimme 5 draw in Vermont marked a notable return: 03 13 24 31 39 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
The numbers in 03 13 24 31 39 cover a wide range (3 to 39) with no repeats.
Why Droughts Matter
Extended gaps are context, not forward-looking - they show where spacing departs from typical cadence. They offer context for distribution stability over time.
Data Notes
The approach: this report summarizes the results logged for Wednesday night, May 6, 2026 with comparison to long-run frequency baselines. It is intended for context, not forecasting.
From Stepzero
Simply put: this reporting is designed to document distribution behavior over time as context for disciplined analysis. The focus is long-horizon context.
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. 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.
Adding to the Long-Term Record
The return of 03 13 24 31 39 expands the archive by one more data point. It is the accumulation of these entries, not a single draw, that defines the reliability of long-horizon analysis.