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Football Predictions Today

Thursday, 14 May 2026 ยท 0 matches analysed

Poisson-based predictions built from each team's last 10 finished matches, home/away splits, and the league's own scoring baseline. Every number you see is a calibrated probability โ€” no black-box confidence scores.

High Confidence (70%+) Medium (55-69%) Low (<55%)
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What's Behind These Predictions

Every prediction on this page is built from the last 10 completed matches for each team โ€” goals scored, goals conceded, home vs. away splits, clean sheets, BTTS rates. From those we derive attack and defense strengths relative to the league's own baseline, feed them into a Poisson model, and read off the probability of every scoreline from 0-0 up to 7-7. The headline prediction is whichever of home/draw/away has the highest mass on that grid.

We show the expected goals (xG) for both sides, the full 1X2 probability breakdown, and the top four most-likely scorelines. You can see every number we use. That's deliberate. Tipster culture thrives on black boxes โ€” "trust my expert pick" with no reasoning. We'd rather show the working. If you want to understand the stats deeper, start with our xG explainer or the broader football stats for betting guide.

What the Confidence Rating Means

The percentage next to each prediction is a calibrated probability from the Poisson model โ€” not a hype metric. 62% means the model literally projects a 62% chance of that outcome happening, summed across the scorelines grid. That lets you compare it directly to bookmaker odds: if the implied probability on a price is below the model's, there's value; if it's above, pass.

  • 70%+ โ€” Large form/xG gap. The model is confident. Look for value at enhanced prices.
  • 55-69% โ€” Clear lean. Double Chance or Draw No Bet are the safer routes.
  • Below 55% โ€” Too close. Either pass or fold into a combo bet like BTTS + Over.

No model gets every match right. If someone claims 85%+ accuracy across all picks, they're lying or cherry-picking. Our goal is to beat the implied probability of the odds โ€” which is where disciplined staking comes in.

Three Markets, One Page

Each match above covers the three most popular football betting markets:

  • Match Result (1X2) โ€” home win, draw, or away win. The beginner's guide covers the basics.
  • Over/Under 2.5 Goals โ€” Poisson gives us the direct probability of 3+ goals from the expected goal rates.
  • BTTS โ€” probability both sides score at least once, computed from the joint Poisson grid.

Looking for something more specific? We also cover Asian Handicap, Correct Score, and Bet Builder strategies in our guides.

Frequently Asked Questions

How accurate are your football predictions?
The Poisson model is the industry standard for football goal-based markets โ€” it doesn't claim to predict every match correctly (nobody can) but it produces calibrated probabilities. High-confidence picks (70%+) have a genuine xG and form gap between the two sides. Lower-confidence picks are closer to coin flips โ€” treat them accordingly.
When are today's predictions updated?
Every time you load this page, it pulls live data and re-runs the Poisson model. Our match database syncs every 15 minutes โ€” if a result came in an hour ago, the form data already reflects it. No caching, no stale tips from yesterday.
Which leagues do you cover for predictions?
Currently six major competitions: Premier League, Champions League, La Liga, Serie A, Bundesliga, and Ligue 1. We focus on leagues where our match data is comprehensive enough to produce meaningful form analysis and stable per-league baselines.
What does BTTS mean in football predictions?
BTTS = Both Teams to Score. We sum the Poisson grid across every cell where both home and away goals are 1 or higher โ€” that gives the probability both sides find the net. Teams with strong attack plus leaky defense produce high BTTS probabilities; clean-sheet specialists suppress them.
What does Over 2.5 Goals mean?
Over 2.5 Goals means the match produces 3 or more total goals. We compute the probability by summing Poisson(home) ร— Poisson(away) across every cell where goals_home + goals_away โ‰ฅ 3. Because this uses expected goals rather than raw averages, it handles home/away asymmetry and sparse-data cases correctly.

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Disclaimer: Predictions are based on statistical analysis and do not guarantee outcomes. Gambling involves risk โ€” always bet responsibly and within your means. 18+ only. Responsible Gambling | BeGambleAware.org