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Guide
How accurate are AI football predictions?
Football is the hardest mainstream sport to predict — and that is exactly why honest accuracy reporting matters more here than anywhere else.
Updated 2026-10-19 · by the Footalytics team
Reality check: what a good number looks like
Across a season, a well-built model picks the right 1X2 outcome roughly 50–55% of the time, and that is genuinely good — the strongest published benchmarks sit in the same range. Draws remain the hardest call. Exact scores, spread over dozens of plausible lines, rarely top 13% for their single most likely outcome.
Hit rate vs calibration: the Brier score
Hit rate only counts whether the top pick landed. The Brier score measures whether the probabilities themselves were honest: a model that says 70% and is right 70% of the time scores better than one that says 90% and is right 60% of the time — even though the second "wins" more picks. Footalytics publishes both, per league and per market.
How we grade ourselves
Official predictions — one per selected match — are generated by the model 24–48 h before kick-off, refreshed once in the final six hours and locked one hour before. After full time they are settled against the real score on the public dashboard: hits and misses, hit rates by league and market, Brier scores, and small-sample warnings below 30 matches. Chat predictions stay private and are never counted.
Red flags in accuracy claims
Ninety-percent claims (impossible over any real sample), no visible misses, records that started yesterday, “VIP” walls in front of the evidence, and paid-tip pages with no method section. A service confident in its numbers shows them graded, in public, including the losses.
Where to see our numbers
The accuracy dashboard is public: settled counts, hit rates for 1X2, over/under 2.5, BTTS and exact score, Brier scores, per-league tables and the most recent graded predictions. The methodology page explains how the model works; the guides cover how to read the numbers.
FAQ
What accuracy is realistic for AI football predictions?
Around 50–55% for 1X2 over a real season, with draws hardest and exact scores rarely above 13% for the top line. Claims far beyond that do not survive honest grading.
What is a Brier score?
A measure of how well-calibrated probabilities are — lower is better, and it rewards honest numbers over confident ones. Random guessing on 1X2 scores about 0.667.
Why do you show missed predictions?
Because a record without misses is marketing, not evidence. Grading every official pick — wins and losses — against real scores is the only way the numbers mean anything.
So is it worth following AI predictions?
As calibrated probabilities and clear explanations, yes — they are a genuine reading of the match. As certainties, no such thing exists in football.