Results and reliability

Verified AI football picks performance

No empty promises: we show real numbers, a track record, and verifiable matches. Choose a pick type, adjust the probability threshold, and see how performance changes.

Data updated on

Engine version Program 3.9 • P2.12 Production · April 07, 2026 Engine versions
Learn reliability Today's AI football predictions overall history

Statistics

Three cues are enough to read performance quickly: wins, total volume, then success rate.

Winning volume Correct results 202 Number of winning picks on settled matches.
Analyzed base Analyzed matches 288 Volume used to judge the selected market and threshold.
Main signal Success rate 70.14% The first number to compare when testing settings.

Filters

Step 1
Choose the pick type

Start with the market you want to evaluate, then refine the threshold below.

Step 2
Higher means fewer picks, but usually stronger quality.
55%
Create profile

Step 3
Keep "All leagues" for the broadest view.

History

Cumulative correct picks

Cumulative curve: a steeper slope means more correct picks over the period.

Matches

FAQ - how to read picks performance

Why a different threshold for each pick type?

Each market has a different difficulty (1X2 vs BTTS vs Over/Under). A tailored threshold makes comparisons more meaningful.

Why show "verifiable" matches?

So you can check everything: transparency is the best protection against marketing hype.

AI football picks performance: Double Chance, DNB, BTTS, Over/Under

Foresportia tracks performance across several AI football pick types (Double Chance, Draw No Bet, 1X2, BTTS, Over 2.5, Under 2.5), with filters by probability threshold and league, plus match-by-match verification.

This page extends the core 1X2 history by showing how Foresportia probabilities behave on derivative markets. The goal is not to stack picks blindly, but to measure how each market reacts to real football results once you control for sample size, league context and the selected threshold. A high win rate on a tiny sample is not the same as durable reliability on a large one.

The verification method is straightforward: each pick type has a clear definition, each threshold is explicit and every displayed result comes from settled matches. That makes it possible to compare Double Chance, DNB, BTTS and Over/Under on a consistent basis, then connect each setting to verifiable fixtures. In practice, this page works as a proof layer for market-specific reading, not as a promise page.