Mathematical Methodology, AI & Verification

Full transparency of our calculations

SwissLotto Prognose uses only traceable, mathematically correct formulas — complemented by our AI-driven engines (recency weighting & hedge engine with 8 methods). On this page you can verify every calculation step by step — we have nothing to hide.

Scientific Background

Our calculation modules are based on established theories with historically documented sources:

• Biorhythm: Three-cycle theory by Dr. Wilhelm Fliess (Physical, 23 days, 1897), Dr. Hermann Swoboda (Emotional, 28 days, 1900) and Alfred Teltscher (Intellectual, 33 days, 1920s).
• Numerology: Pythagorean system (Life Path, Destiny, Soul, Personality numbers) including Master Numbers 11/22/33.
• Astrology: Ascendant calculation using the VSOP87 Astronomia ephemeris for highest astronomical accuracy.

Formulas Used

The biorhythm calculation uses a pure sine function: sin(2π × days ÷ cycle length) × 100. Days = exact difference between birth date and target date (UTC midnight). Cycle length = 23 (Physical), 28 (Emotional) or 33 (Intellectual). Result: value between −100 % (low point) and +100 % (peak). Time-zone, DST and leap-year safe.

Recency weighting — fresh data counts more

Every new draw gets full influence. Over time the influence of older draws fades — fresh data weighs more. The forecast stays aligned with current behaviour instead of patterns from the 80s.

Yesterday = 1.00 (100 %), 1 year ago = 0.50 (50 %), 2 years ago = 0.25 (25 %), 5 years ago = 0.03 (3 %).

Hedge engine — 8 AI methods working together

After every official draw, the AI compares the suggestions of all 8 methods with the actually drawn numbers — and automatically adjusts the weight of each method. This currently produces the following ranking:

• Frequency analysis: Which numbers came up most historically?
• Poisson: Probability of rare clusters and gaps.
• Markov chains: Which number typically follows which?
• Monte Carlo: Thousands of simulated random draws.
• Bayesian inference: Combines prior knowledge with each new draw.
• Fourier cycles: Rhythmic patterns and waves over time.
• Regression: Detects long-term trends in the data.
• Ensemble: Majority decision from all other methods.

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