Nantes v Saint-Étienne
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 Nantes drew with Saint-Étienne 2–2, the SharpXI model made 14 confident calls on the player markets and 11 landed — the strongest being Matthis Abline for 1+ shots total (85%, had 2). Its clearest miss: Sorba Thomas for 1+ fouls drawn (78%, had 0). 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 |
|---|---|---|---|---|---|
| Matthis Abline | shots total | 1+ | 85% | 2 | ✓ |
| Ibrahim Sissoko | fouls committed | 1+ | 82% | 2 | ✓ |
| Marcus Coco | fouls drawn | 1+ | 79% | 1 | ✓ |
| Sorba Thomas | fouls drawn | 1+ | 78% | 0 | ✗ |
| Marcus Coco | fouls committed | 1+ | 77% | 1 | ✓ |
| Augusto Douglas | fouls drawn | 1+ | 77% | 3 | ✓ |
| Nicolas Cozza | fouls drawn | 1+ | 77% | 1 | ✓ |
| Ibrahim Sissoko | shots total | 1+ | 77% | 3 | ✓ |
| Augusto Douglas | fouls committed | 1+ | 76% | 1 | ✓ |
| Johann Lepenant | fouls drawn | 1+ | 76% | 0 | ✗ |
| Matthis Abline | fouls drawn | 1+ | 75% | 0 | ✗ |
| Ibrahim Sissoko | fouls drawn | 1+ | 74% | 3 | ✓ |
| Moses Simon | fouls drawn | 1+ | 73% | 3 | ✓ |
| Moses Simon | shots total | 1+ | 72% | 3 | ✓ |
How these are modelled: Shots total · Fouls committed · Fouls drawn
Team & match markets
| Market | Line | Model | Actual | Result |
|---|---|---|---|---|
| Match goals | O2.5 | 46% | 4 goals | ✓ |
| BTTS | Yes | 36% | Yes | ✓ |
| Match cards | O4.5 | 31% | 5 cards | ✓ |
How these are modelled: Match goals · Match cards
Dig deeper
Past meetings
- Saint-Étienne 1–1 Nantes Jan 2025
Frequently asked
How did the SharpXI model do on Nantes v Saint-Étienne?
11 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 Nantes v Saint-Étienne?
The most confident call it got wrong was Sorba Thomas at 78% for fouls drawn — shown in the same table as the hits, marked with a cross. A record that hides its misses isn't a record, so we don't.
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.