Tri-State Gimme 5 Results
On Thursday night, December 11, 2025, the Tri-State Gimme 5 draw in Vermont produced a notable return: 01 03 14 21 38 after days of absence. Against an expected cadence of 1 in 575,757 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Winning numbers for 1 draw on December 11, 2025 in Vermont.
Draw times: Evening.
Our take on the Tri-State Gimme 5 results
December 11, 2025Tri-State Gimme 5 report — Thursday night, December 11, 2025: 01 03 14 21 38 shows a notable pattern
On Thursday night, December 11, 2025, the Tri-State Gimme 5 draw in Vermont produced a notable return: 01 03 14 21 38 after days of absence. Against an expected cadence of 1 in 575,757 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Overview
On Thursday night, December 11, 2025, the Tri-State Gimme 5 draw in Vermont produced a notable return: 01 03 14 21 38 after days of absence. Against an expected cadence of 1 in 575,757 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Combo Profile
The numbers in 01 03 14 21 38 cover a wide range (1 to 38) with no repeats.
Why Droughts Matter
Long droughts are descriptive, not a signal - they show how distribution tails behave. Their value is in long-horizon tracking.
Data Notes
The approach: this analysis documents outcomes logged on Thursday night, December 11, 2025 with benchmarking against long-run cadence. The intent is documentation, not forecasting.
From Stepzero
At its core: these reports are built to keep the record consistent over time as context for disciplined analysis. It is meant to inform, not 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.
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 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
Across the long-term record, this entry adds another archive entry to the long-run dataset. Stability comes from the growing record, not any one draw.