Lille v Montpellier
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 Lille beat Montpellier 1–0, the SharpXI model made 14 confident calls on the player markets and 12 landed — the strongest being Chuba Akpom for 1+ fouls drawn (84%, had 1). Its clearest miss: Tanguy Coulibaly for 1+ fouls committed (86%, 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 |
|---|---|---|---|---|---|
| Tanguy Coulibaly | fouls committed | 1+ | 86% | 0 | ✗ |
| Chuba Akpom | fouls drawn | 1+ | 84% | 1 | ✓ |
| Teji Savanier | fouls drawn | 1+ | 84% | 2 | ✓ |
| André Gomes | fouls committed | 1+ | 83% | 2 | ✓ |
| Rémy Cabella | fouls committed | 1+ | 80% | 0 | ✗ |
| Rabby Nzingoula | fouls committed | 1+ | 80% | 3 | ✓ |
| Jonathan David | shots total | 1+ | 80% | 3 | ✓ |
| Andy Delort | fouls committed | 1+ | 80% | 1 | ✓ |
| Rémy Cabella | shots total | 1+ | 80% | 2 | ✓ |
| Benjamin André | fouls committed | 1+ | 79% | 1 | ✓ |
| Chuba Akpom | shots total | 1+ | 78% | 1 | ✓ |
| Rémy Cabella | fouls drawn | 1+ | 77% | 3 | ✓ |
| Ayyoub Bouaddi | fouls committed | 1+ | 77% | 1 | ✓ |
| Boubakar Kouyaté | fouls committed | 1+ | 77% | 2 | ✓ |
How these are modelled: Fouls committed · Fouls drawn · Shots total
Team & match markets
| Market | Line | Model | Actual | Result |
|---|---|---|---|---|
| Match cards | O4.5 | 78% | 5 cards | ✓ |
| Match goals | O2.5 | 63% | 1 goals | ✗ |
| BTTS | Yes | 59% | No | ✗ |
How these are modelled: Match cards · Match goals
Dig deeper
Past meetings
- Montpellier 2–2 Lille Dec 2024
- Montpellier 0–0 Lille Jan 2024
- Lille 1–0 Montpellier Sep 2023
- Lille 2–1 Montpellier Apr 2023
- Montpellier 1–3 Lille Sep 2022
Frequently asked
How did the SharpXI model do on Lille v Montpellier?
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 Lille v Montpellier?
The most confident call it got wrong was Tanguy Coulibaly at 86% for fouls committed — 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.