Open Access

All predictions, models and accuracy data are currently open so you can verify our results first-hand. No signup, no paywall — full transparency.

Subscription plans & API access launch August 10, 2026.

Signal Analytics

Return analysis across markets, leagues and allocation methods
Total Signals
5,612
1,672 fixtures analysed
Win Rate
39.1%
2,193 / 5,612 correct
Weighted average across all markets. Signals on low-probability outcomes (draws, clean sheets) lower this number — what determines profitability is Yield, not Win Rate.
Yield (Equal-Weight)
-9.2%
Positive = net profit per unit risked
Growth (Proportional)
-84.9%
Risk-adjusted allocation
7D 30D 90D All
2026-06-10 to 2026-07-09 (30 days)
Cumulative Yield
Return by Market
Return by League
Top 15 by signal count
Signal Strength Distribution
Model advantage vs. implied probability

Edge = the difference between the model's estimated probability and the market-implied probability (1/odds). Bars show how many signals fall in each edge range; the line shows the win rate for each range. Note: win rate is not expected to increase linearly with edge — high-edge signals often target low-probability outcomes (draws, clean sheets) where the model sees large value relative to the market but the base win rate remains low. When a bucket contains fewer than ~50 signals, the win rate line may fluctuate significantly due to small sample size.

Return by Country
Methodology

A signal is generated when our model identifies an edge of at least 2% between its estimated probability and the market-implied probability. Only predictions created before the match starts are included — no backtesting, no hindsight.

For informational and educational purposes only. Past statistical performance does not guarantee future results. This does not constitute financial advice.

Last updated 20 hours ago