The formula
Expected value is one line of arithmetic:
EV = (chance of winning × profit if it wins) − (chance of losing × stake)
Run it on the coin flip above. Heads pays 2.10, so $100 staked wins $110 profit half the time and loses $100 the other half: (0.5 × $110) − (0.5 × $100) = +$5 per $100 staked. Positive means the price is better than the outcome deserves. That is the only thing we look for.
Why volume matters more than any single bet
Variance dominates small samples. A +EV bet at +5% can lose ten times in a row before the math asserts itself. That's why we post 1,000+ bets per day across both feeds. The Law of Large Numbers applies: with enough bets at positive expectation, realised returns converge to expected returns.
Practical implication for the member: staking flat per bet at a small fraction of bankroll is how the math compounds. Most members size at 1–2% of bankroll per +EV pick, scaled by edge size via Kelly fractioning.
How we price probabilities
Our pricing models combine:
- Sharp-book consensus: books with the highest limits and lowest margins (Pinnacle, Betfair Exchange) are the closest proxies to fair price. We weight them heavily.
- Devigging: removing the bookmaker margin from their own odds to recover implied probabilities, then aggregating across multiple books.
- Market-specific models: for player props and niche markets where sharp-book lines don't exist, our own statistical models price the event from historical and situational data.
The output is a fair probability per outcome. We compare every book we cover against the fair price, every second. The gaps that clear our threshold are posted.
What we don't do
- No tipsters. No human cherry-picking. No “locks of the day.”
- No guaranteed results. Past performance does not guarantee future results.
- No proprietary mystery box. The methodology is on this page. The execution is in the volume and the speed.
Further reading
The concepts here are well-established in quantitative finance and sports analytics. Open primers we recommend:
- Joseph Buchdahl, Football Data: methodology essays on devigging and value detection.
- Levitt & Dubner work on Why Do Bettors Place Bad Bets? (academic background on bookmaker margin and market efficiency).
- Kelly, J.L. (1956), A New Interpretation of Information Rate, the original Kelly criterion for stake sizing.
The bookmaker prices the vig. The model prices the probability. When they disagree, that's the bet.