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🤖 ML + RL

How our model tips

E-E-A-T: transparency on data, models and value bets

1. Data basis

We use live fixture data, form, head-to-head, standings and multi-bookmaker odds. We estimate probabilities and compare them to the market — the core of value betting.

2. Machine Learning (ML)

Classic ML signals (ELO-like strength, form, home advantage) estimate 1X2 as well as markets such as over/under and BTTS. Models are updated as seasons progress.

3. Reinforcement Learning (RL)

RL components evaluate which tips deliver the best long-term expected value under uncertainty and odds movement — not only the single most likely outcome.

4. AI analysis

A large language model (LLM) synthesises all signals: injuries, line-ups, form, H2H and odds. It produces the written match analysis, confidence and extra markets (e.g. scorers, corners, cards) — a readable layer on top of pure ML/RL numbers.

5. Value Bets & Transparenz

A value bet appears when our estimated probability exceeds the probability implied by the odds. Winning tips are published under Results, including monthly archives.

6. Leagues & next steps

Stable league landing pages and archives give Google and users structure — even when individual tips change daily.

⚠️ This page is not an invitation to gamble. All predictions are non-binding. 18+