FC Porto
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FC Porto to win · 85% model probability · odds 1.14 · edge -2.7 pts
Last updated 19 minutes ago
Strike rate 70.7% from 610 selections, ROI -4.1% to level stakes. Full record for this market.
FC Porto to win · 85% model probability · odds 1.14 · edge -2.7 pts
Paris Saint Germain to win · 72% model probability · odds 1.33 · edge -3.2 pts
Missing — Paris Saint Germain: L. Digne (missing fixture), Nuno Mendes (missing fixture), D. Doué (questionable) · Monaco: Takumi Minamino (missing fixture), Mohammed Salisu (missing fixture), Ansu Fati (missing fixture) +2 more
Lyon to win · 68% model probability · odds 1.42 · edge -2.4 pts
Missing — Lyon: Keito Nakamura (missing fixture), J. Duranville (missing fixture), Alejandro Gomes Rodriguez (missing fixture) +5 more · Auxerre: A. Tuanzebe (missing fixture), A. Dioussé (missing fixture), F. Sierralta (missing fixture) +4 more
Real Madrid to win · 67% model probability · odds 1.38 · edge -5.5 pts ▼ Steaming 18.2%
Missing — Real Betis: Dani Ceballos (missing fixture), G. Lo Celso (missing fixture), Aitor Ruibal (missing fixture) +5 more · Real Madrid: Éder Militão (missing fixture), F. Mendy (missing fixture), A. Tchouaméni (missing fixture) +4 more
VfB Stuttgart to win · 66% model probability · odds 1.45 · edge -3 pts
Missing — VfB Stuttgart: D. Zagadou (missing fixture), C. Führich (questionable), N. Nartey (missing fixture) +7 more · 1. FC Köln: L. Waldschmidt (missing fixture), Timo Hübers (missing fixture), T. Dallinga (questionable) +2 more
Liverpool to win · 60% model probability · odds 1.50 · edge -6.7 pts
Missing — Ipswich: Florentino (questionable), J. Taylor (missing fixture), A. Matusiwa (missing fixture) +1 more · Liverpool: J. Gomez (missing fixture), F. Chiesa (missing fixture), B. Barcola (missing fixture) +4 more
Home, draw or away. Every other football market is a derivative of this one, and it remains the hardest to beat, because it attracts the most money and therefore the sharpest prices. The margin a bookmaker builds into a Premier League 1X2 market is often under five percent, thinner than almost anything else on the coupon. Beating it takes more than opinion, which is where the model comes in and where reputations go wrong.
The model prices all three outcomes from team ratings built on results, scoring rates, opponent quality and home advantage measured league by league. A selection appears on this page when the model's probability for an outcome clears our threshold and stands meaningfully above what the odds imply. That second condition matters more than the first. A 65% favourite priced as a 72% favourite is a losing bet forever, while a 45% home side priced as a 38% one is the kind of unglamorous pick this page exists for.
Expect the selections to look unfashionable. Ratings have no memory of last season's table and no affection for big clubs, so a well-drilled promoted side at home can out-rate a famous name in poor form. The lower English divisions we track are particularly fertile, because thinner betting markets leave more pricing gaps than the heavily traded top flights. That is not a flaw in the approach; it is the approach.
Double chance variants (home or draw, away or draw) appear when the model's combined probability justifies the shorter price. They suit fixtures where the model is confident one side will not win rather than confident about the winner, a distinction the scoreline grid makes naturally.
The 1X2 record is published in full, settled against publication odds, and it is the only advertisement this page gets. If you want the mechanics, the method page explains how ratings become probabilities in plain English, and the draw page covers the outcome most bettors systematically avoid, usually to their cost, since draws are the most consistently mispriced result in football.
They are selections for this market produced by a statistical model rather than a tipster. The model estimates a probability for every fixture it prices, and a selection appears here when that probability clears the market threshold. The market itself is explained in plain English in our glossary.
A model rates every team from recent results, converts those ratings into goal expectancies for each fixture, and turns the expectancies into probabilities for this market. Selections are archived at kickoff and never edited afterwards.
Over its full recorded history this market has a 70.7% strike rate from 610 settled selections, at -4.1% ROI to level stakes. Every settled selection is published in the results archive, including the losing runs.