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Ligue 1 24/25

Toulouse v Stade de Reims

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.

Toulouse1 – 0 Stade de Reims 3 Nov 2024
12/14
of the model's most-confident calls landed. Every one was published before kick-off and priced the same way as every other fixture. A single game is noise, not a verdict — the season-long record is on the track record.

Before Toulouse beat Stade de Reims 1–0, the SharpXI model made 14 confident calls on the player markets and 12 landed — the strongest being Zakaria Aboukhlal for 1+ shots total (95%, had 6). Its clearest miss: Yann Gboho for 1+ fouls drawn (91%, 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.

Match officials+12% cards vs the league average
Mathieu Vernice refereed this match 4.35cards a gameleague 3.87 63games
Mathieu Vernice's card record
See the full player stats boardBoth likely XIs side by side — hit rates over your chosen window, add to your slip ›

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.

PlayerMarketLineModel ActualResult
Zakaria Aboukhlal shots total 1+ 95% 6 ✓
Cristian Cásseres Jr. tackles 1+ 95% 4 ✓
Keito Nakamura shots total 1+ 94% 1 ✓
Joshua King shots total 1+ 94% 2 ✓
Waren Kamanzi tackles 1+ 93% 2 ✓
Amadou Koné fouls drawn 1+ 91% 3 ✓
Yann Gboho fouls drawn 1+ 91% 0 ✗
Djibril Sidibé tackles 1+ 88% 1 ✓
Oumar Diakité fouls committed 1+ 87% 3 ✓
Yann Gboho shots total 1+ 84% 0 ✗
Oumar Diakité shots total 1+ 84% 2 ✓
Emmanuel Agbadou tackles 1+ 83% 1 ✓
Amadou Koné tackles 1+ 83% 5 ✓
Valentin Atangana Edoa tackles 1+ 83% 2 ✓

How these are modelled: Shots total Tackles Fouls drawn Fouls committed

Team & match markets

MarketLineModel ActualResult
BTTS Yes 51% No ✗
Match goals O2.5 49% 1 goals ✗
Match cards O4.5 41% 3 cards ✗

How these are modelled: BTTS Match cards

Dig deeper

Past meetings

Frequently asked

How did the SharpXI model do on Toulouse v Stade de Reims?

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 Toulouse v Stade de Reims?

The most confident call it got wrong was Yann Gboho at 91% 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.