Olympique de Marseille v Paris FC
How the SharpXI model rated this Ligue 1 fixture — every call it made on shots, cards and fouls, set against what actually happened on the day.
Before Olympique de Marseille lost to Paris FC 2–3, the SharpXI model made 14 confident calls on the player markets and 14 landed — the strongest being Pierre Lees Melou for 1+ tackles (95%, had 2). Every probability here was published before kick-off, priced the same way as every other fixture — one game is noise, not a verdict.
Player markets — the model's calls
Each probability is the model's own number for the headline (1+) line, before any bookmaker margin. The result column is what the player actually recorded.
| Player | Market | Line | Model | Actual | Result |
|---|---|---|---|---|---|
| Pierre Lees Melou | tackles | 1+ | 95% | 2 | ✓ |
| Lassine Sinayoko | shots total | 1+ | 94% | 4 | ✓ |
| Luca Koleosho | tackles | 1+ | 92% | 1 | ✓ |
| Amine Gouiri | shots total | 1+ | 92% | 5 | ✓ |
| Adama Camara | tackles | 1+ | 88% | 8 | ✓ |
| Pablo Pagis | shots total | 1+ | 87% | 2 | ✓ |
| Luca Koleosho | shots total | 1+ | 84% | 4 | ✓ |
| Igor Paixão | shots total | 1+ | 84% | 1 | ✓ |
| Hamari Traoré | tackles | 1+ | 83% | 1 | ✓ |
| Ilan Kebbal | fouls drawn | 1+ | 83% | 1 | ✓ |
| Amine Harit | fouls drawn | 1+ | 83% | 2 | ✓ |
| Pablo Pagis | fouls drawn | 1+ | 83% | 1 | ✓ |
| Emerson | tackles | 1+ | 82% | 2 | ✓ |
| Rudy Matondo | tackles | 1+ | 82% | 2 | ✓ |
How these are modelled: Tackles Shots total Fouls drawn
Team & match markets
| Market | Line | Model | Actual | Result |
|---|---|---|---|---|
| Match goals | O2.5 | 62% | 5 goals | ✓ |
| BTTS | Yes | 60% | Yes | ✓ |
| Match cards | O4.5 | 31% | 2 cards | ✗ |
How these are modelled: Match goals Match cards
Dig deeper
Past meetings
- Paris FC 2–2 Olympique de Marseille Jan 2026
- Olympique de Marseille 5–2 Paris FC Aug 2025
Frequently asked
How did the SharpXI model do on Olympique de Marseille v Paris FC?
14 of its 14 most-confident calls landed. The board on this page lists every one with the model's pre-kickoff probability next to what actually happened, hits and misses in the same table.
What did the model get wrong on Olympique de Marseille v Paris FC?
Every one of its confident calls landed this time — a single strong game, not a verdict. When the model does miss, those rows sit in the same table as the hits, marked with a cross; we never hide them.
Are these probabilities hindsight?
No. Each one is the number the model produced from data available before kick-off, using the same settings as every other fixture on the site — nothing was refitted after the result. That is the only way a per-match report means anything.
Does one match tell you if the model is any good in the Ligue 1?
No, and we'd rather say so. A single fixture is a handful of calls and mostly noise; the season-long, market-by-market record — including the markets that fail to beat a naive guess — is on the track record page.
SharpXI models probabilities from public match data; it does not take bets or guarantee outcomes. Prices are entered per leg in the tool. 18+ — please gamble responsibly.