Real-Time Edge Signals Scanner

Free edge calculator and live demo simulator. Compute the gap between fair probability and market price, account for fees and slippage, and get a quarter-Kelly position size with a signal verdict.

Live Demo Feed (Synthetic)

This panel demonstrates what a real-time edge scanner output looks like across 11 sports. The signals are randomly generated for demonstration; live signals on production trading bots come from actual market and game-state data.

How the verdict logic works

The scanner classifies every candidate signal into one of three verdicts based on effective edge after costs:

• PASS — effective edge between 5¢ and 18¢. The middle of the distribution is where genuine market mispricing lives. Fire the trade with quarter-Kelly sizing.
• SKIP-low — effective edge below 5¢. The detected gap is too small to clear costs reliably. Even if it is real, fees and slippage will eat it.
• SKIP-high — effective edge above 18¢. Counterintuitively, the very largest detected edges are usually the model being wrong, not real opportunity. We learned this expensively on tennis: ATP edges between 20-25¢ ran 31% win rate over 13 trades, while edges between 15-20¢ ran 59% with strong dollar profit.

The math behind it

Edge in cents per share is the model's fair probability (in cents) minus the market ask, minus your costs:

raw_edge_c     = fair_prob * 100 - ask_price_c
cost_c         = taker_fee_c + expected_slippage_c
effective_edge = raw_edge_c - cost_c

Quarter-Kelly position size is the standard professional sizing for situations where your probability estimate has error (which it always does):

edge          = fair_prob - ask_price
profit_per_$  = 1 - ask_price
full_kelly    = edge / profit_per_$
quarter_kelly = 0.25 * full_kelly
position_size = bankroll * quarter_kelly

The 0.25 multiplier sacrifices about 25% of theoretical growth to eliminate roughly 90% of the ruin risk. Full Kelly assumes your probability is exactly correct — it is not, ever. More on this in our trading bot guide.