SKAI Methods Distribution & Temporal Analysis

Distribution & Temporal Analysis

This domain focuses on how number behavior changes over time. It measures long-term distribution, short-term shifts, and absence/re-entry dynamics — helping SKAI separate stable signals from noise.

frequency recency weighting skip & gap rolling windows

What this domain measures

Distribution & temporal analysis looks at how outcomes behave across time horizons. SKAI uses it to understand whether a number’s recent activity is consistent with its longer-term baseline.

  • Baseline distribution: long-term frequency behavior.
  • Recent drift: short-term movement versus baseline.
  • Absence dynamics: gaps, skips, and re-entry timing.
  • Window stability: whether signals hold across different draw windows.

Key methods in this domain

Frequency & Recency Modeling

Models long-term frequency with adaptive weighting that prioritizes recent behavior without ignoring baseline.

Skip & Gap Distance Analysis

Measures how long numbers remain absent and how often they re-enter after different gap lengths.

Rolling Window Analysis

Recomputes signals across moving draw windows to detect emerging shifts and reduce window overfitting.

Hit-Rate Trend Analysis

Evaluates consistency of returns over time, not just raw appearance counts.

Volatility Monitoring

Flags periods where distributions become unstable, helping SKAI avoid overweighting transient streaks.

Window Cross-Validation

Tests whether a signal holds across multiple window sizes, improving robustness.

How SKAI uses these signals

SKAI treats temporal signals as one layer in a larger system. These measures influence rankings only when they remain stable across windows and align with broader distribution behavior. When signals conflict, SKAI reduces their weight instead of forcing a “confident” prediction.

  • Signals are blended — not used in isolation.
  • Short-term spikes are discounted if they fail stability checks.
  • Ranking emphasizes repeatable behavior over narrative streaks.

Where you’ll see this in LottoExpert

These signals typically appear inside SKAI ranking panels, skip & hit modules, and trend-aware charts. When available, LottoExpert surfaces the most relevant time horizon so you can understand what is being weighted.

  • SKAI ranking and probability panels
  • Skip & hit analysis modules
  • Rolling window charts and trend views

Responsible use: lotteries are random and no method can guarantee outcomes. SKAI is designed to help interpret probability signals — with clarity and control.

Built on probabilities — not promises.