Nice v Lorient
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 Nice drew with Lorient 0–0, the SharpXI model made 14 confident calls on the player markets and 12 landed — the strongest being Zoumana Diallo for 1+ shots total (92%, had 1). Its clearest miss: Melvin Bard for 1+ tackles (88%, 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 |
|---|---|---|---|---|---|
| Zoumana Diallo | shots total | 1+ | 92% | 1 | ✓ |
| Antoine Mendy | tackles | 1+ | 88% | 4 | ✓ |
| Dembo Sylla | tackles | 1+ | 88% | 1 | ✓ |
| Melvin Bard | tackles | 1+ | 88% | 0 | ✗ |
| Arthur Avom Ebong | tackles | 1+ | 88% | 2 | ✓ |
| Gabin Bernardeau | tackles | 1+ | 88% | 0 | ✗ |
| Aiyegun Tosin | shots total | 1+ | 87% | 1 | ✓ |
| Sofiane Diop | shots total | 1+ | 84% | 1 | ✓ |
| Mohamed Ali Cho | shots total | 1+ | 84% | 1 | ✓ |
| Gauthier Hein | shots total | 1+ | 84% | 1 | ✓ |
| Théo Le Bris | tackles | 1+ | 83% | 1 | ✓ |
| Djibril Coulibaly | tackles | 1+ | 83% | 1 | ✓ |
| Jonathan Clauss | tackles | 1+ | 83% | 2 | ✓ |
| Everton Pereira | tackles | 1+ | 82% | 2 | ✓ |
How these are modelled: Shots total Tackles
Team & match markets
| Market | Line | Model | Actual | Result |
|---|---|---|---|---|
| BTTS | Yes | 53% | No | ✗ |
| Match goals | O2.5 | 48% | 0 goals | ✗ |
| Match cards | O4.5 | 27% | 1 cards | ✗ |
How these are modelled: BTTS Match cards
Dig deeper
Past meetings
- Nice 3–3 Lorient Feb 2026
- Lorient 3–1 Nice Nov 2025
- Nice 3–0 Lorient Apr 2024
- Lorient 1–1 Nice Aug 2023
- Nice 1–1 Lorient Mar 2023
- Lorient 1–2 Nice Oct 2022
Frequently asked
How did the SharpXI model do on Nice v Lorient?
12 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 Nice v Lorient?
The most confident call it got wrong was Melvin Bard at 88% for tackles — 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.