Montpellier v Metz
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 Montpellier beat Metz 3–0, the SharpXI model made 14 confident calls on the player markets and 13 landed — the strongest being Arnaud Nordin for 1+ fouls drawn (86%, had 1). Its clearest miss: Arthur Atta for 1+ fouls committed (76%, 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 |
|---|---|---|---|---|---|
| Arnaud Nordin | fouls drawn | 1+ | 86% | 1 | ✓ |
| Teji Savanier | fouls drawn | 1+ | 84% | 2 | ✓ |
| Jordan Ferri | fouls committed | 1+ | 80% | 2 | ✓ |
| Teji Savanier | shots total | 1+ | 80% | 3 | ✓ |
| Danley Jean Jacques | fouls committed | 1+ | 80% | 1 | ✓ |
| Georges Mikautadze | shots total | 1+ | 80% | 6 | ✓ |
| Joel Asoro | fouls committed | 1+ | 79% | 1 | ✓ |
| Lamine Camara | fouls committed | 1+ | 79% | 3 | ✓ |
| Joseph N'Duquidi | fouls committed | 1+ | 78% | 1 | ✓ |
| Didier Lamkel Zé | shots total | 1+ | 78% | 2 | ✓ |
| Arnaud Nordin | shots total | 1+ | 78% | 1 | ✓ |
| Mousa Tamari | fouls drawn | 1+ | 77% | 2 | ✓ |
| Didier Lamkel Zé | fouls committed | 1+ | 76% | 1 | ✓ |
| Arthur Atta | fouls committed | 1+ | 76% | 0 | ✗ |
How these are modelled: Fouls drawn · Fouls committed · Shots total
Team & match markets
| Market | Line | Model | Actual | Result |
|---|---|---|---|---|
| Match goals | O2.5 | 43% | 3 goals | ✓ |
| BTTS | Yes | 43% | No | ✗ |
| Match cards | O4.5 | 28% | 6 cards | ✓ |
How these are modelled: Match goals · Match cards
Dig deeper
Past meetings
- Metz 0–1 Montpellier Dec 2023
Frequently asked
How did the SharpXI model do on Montpellier v Metz?
13 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 Montpellier v Metz?
The most confident call it got wrong was Arthur Atta at 76% 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.