Ligue 1 player-market outlook — shots, fouls, tackles and the players who lead them
Not all player markets deserve your attention equally. This page covers the ones the model demonstrably beats — shots on target, total shots, fouls and tackles, where the public track record runs double digits ahead of the baseline — and maps who led them last season, how often their 1+ lines actually landed, and the short list of players who led more than one. It's form, not prophecy: these numbers describe what happened, and the model only prices a bet once there's a real opponent and a real price. But the season is long, profiles are sticky, and the punter who knows this map in August is reading a different game from the one who doesn't.
These are 25/26 Ligue 1 rates for players with at least 10 starts, ordered by output per 90. Hit rate is how often the 1+ line would have landed in those starts. Teams shown are last season's; summer signings without a Ligue 1 history appear once they play. This is descriptive form — the model prices each fixture against its actual opponent in-season, which is where the real edge is found.
On last season's numbers (25/26 Ligue 1), Mason Greenwood (Olympique de Marseille) tops the shots-on-target watchlist — 1+ shot on target in 89% of starts, and Ahmadou Bamba Dieng (Lorient) featured across 2 of the value markets. It's a pre-season map from completed matches, not a prediction.
Players who lead more than one value market
One column is a stat; two is a profile. A player who leads several value markets gives you more ways in — different lines, different prices, sometimes only one of them mispriced — and carries one warning worth knowing: those legs travel together. The match that delivers the shots tends to deliver the fouls, and bookmakers price that correlation into same-match combinations. The bet builder guide covers the trap.
| Player | Team | Leads these markets |
|---|---|---|
| Ahmadou Bamba Dieng | Lorient | Shots on target, Total shots |
| Boubacar Traoré | Metz | Fouls committed, Tackles |
| Bradley Barcola | Paris Saint-Germain | Shots on target, Total shots |
| Breel Embolo | Stade Rennais | Fouls committed, Fouls won |
| Emersonn | Toulouse | Total shots, Fouls committed |
| Endrick | Olympique Lyonnais | Shots on target, Total shots |
| Folarin Balogun | AS Monaco | Shots on target, Total shots |
| Gonçalo Ramos | Paris Saint-Germain | Shots on target, Total shots |
| Khvicha Kvaratskhelia | Paris Saint-Germain | Shots on target, Total shots |
| Mason Greenwood | Olympique de Marseille | Shots on target, Total shots |
| Ousmane Dembélé | Paris Saint-Germain | Shots on target, Total shots |
| Sofiane Boufal | Le Havre | Fouls committed, Fouls won |
Shots on target — the leaders
In Ligue 1, Endrick (Olympique Lyonnais) leads at 1.91 per 90, ahead of Elye Wahi (1.77).
Forwards own this list, as they should — but the column that separates a stat from a bet is the hit rate. A gaudy per-90 built on a few wild afternoons reads very differently from the same number spread evenly across thirty starts, and the 1+ line only pays the second kind. Prices here are short and the market's attention is heaviest, so the edge is in precision: how we model shots on target is the full walk.
| Player | Team | Per 90 | 1+ hit rate | Starts |
|---|---|---|---|---|
| Endrick forward | Olympique Lyonnais | 1.91 | 86% | 14 |
| Elye Wahi forward | Nice | 1.77 | 55% | 11 |
| Ahmadou Bamba Dieng forward | Lorient | 1.77 | 73% | 15 |
| Khvicha Kvaratskhelia forward | Paris Saint-Germain | 1.76 | 67% | 15 |
| Mason Greenwood midfielder | Olympique de Marseille | 1.75 | 89% | 27 |
| Gonçalo Ramos forward | Paris Saint-Germain | 1.70 | 62% | 13 |
| Bradley Barcola forward | Paris Saint-Germain | 1.59 | 72% | 18 |
| Odsonne Édouard forward | RC Lens | 1.53 | 80% | 20 |
| Ousmane Dembélé forward | Paris Saint-Germain | 1.53 | 80% | 10 |
| Pierre-Emerick Aubameyang forward | Olympique de Marseille | 1.50 | 68% | 22 |
| Esteban Lepaul forward | Stade Rennais | 1.30 | 77% | 30 |
| Folarin Balogun forward | AS Monaco | 1.28 | 75% | 24 |
How SharpXI models shots on target
Total shots — the leaders
In Ligue 1, Mason Greenwood (Olympique de Marseille) leads at 4.19 per 90, ahead of Gonçalo Ramos (3.95).
The volume market — every attempt counts, so the ladder runs deeper (1+, 2+, 3+) and midfielders who shoot on sight climb a list that shots on target keeps them off. Notice how many leaders sit at or near a 100% hit rate on 1+: that line is close to a formality at the top, which is exactly why the interesting prices usually live further up the ladder, where the distribution's tail decides the bet.
| Player | Team | Per 90 | 1+ hit rate | Starts |
|---|---|---|---|---|
| Mason Greenwood midfielder | Olympique de Marseille | 4.19 | 100% | 27 |
| Gonçalo Ramos forward | Paris Saint-Germain | 3.95 | 100% | 13 |
| Khvicha Kvaratskhelia forward | Paris Saint-Germain | 3.94 | 93% | 15 |
| Ousmane Dembélé forward | Paris Saint-Germain | 3.81 | 90% | 10 |
| Endrick forward | Olympique Lyonnais | 3.68 | 93% | 14 |
| Désiré Doué midfielder | Paris Saint-Germain | 3.65 | 86% | 14 |
| Bradley Barcola forward | Paris Saint-Germain | 3.45 | 89% | 18 |
| Ahmadou Bamba Dieng forward | Lorient | 3.39 | 93% | 15 |
| Emersonn forward | Toulouse | 3.11 | 80% | 15 |
| Folarin Balogun forward | AS Monaco | 3.09 | 92% | 24 |
| Matthis Abline forward | Nantes | 3.06 | 93% | 27 |
| Pablo Pagis forward | Lorient | 3.00 | 86% | 22 |
How SharpXI models total shots
Fouls committed — the leaders
In Ligue 1, Santiago Hidalgo (Toulouse) leads at 2.81 per 90, ahead of Dayann Methalie (2.73).
The folklore says fouling belongs to centre-halves; the table says otherwise. The leaders are midfielders and pressing forwards — the players making challenges in the most contested third of the pitch — and the market, which spends its attention on goals and shots, prices these lines coarsely. That neglect is the whole reason fouls are among the model's strongest markets: every foul is two stats explains the machinery.
| Player | Team | Per 90 | 1+ hit rate | Starts |
|---|---|---|---|---|
| Santiago Hidalgo forward | Toulouse | 2.81 | 77% | 13 |
| Dayann Methalie midfielder | Toulouse | 2.73 | 86% | 21 |
| Nicolás Tagliafico defender | Olympique Lyonnais | 2.45 | 92% | 13 |
| Emersonn forward | Toulouse | 2.39 | 87% | 15 |
| Yassine Kechta midfielder | Le Havre | 2.34 | 86% | 14 |
| Breel Embolo forward | Stade Rennais | 2.31 | 85% | 20 |
| Danny Namaso midfielder | Auxerre | 2.28 | 93% | 29 |
| Remy Labeau Lascary forward | Stade Brestois | 2.18 | 80% | 10 |
| Prosper Peter forward | Angers | 2.12 | 67% | 12 |
| Sofiane Boufal midfielder | Le Havre | 2.10 | 92% | 13 |
| Ludovic Ajorque forward | Stade Brestois | 2.07 | 81% | 32 |
| Boubacar Traoré midfielder | Metz | 2.07 | 73% | 15 |
How SharpXI models fouls committed
Fouls won — the leaders
In Ligue 1, Afonso Moreira (Olympique Lyonnais) leads at 2.98 per 90, ahead of Sofiane Boufal (2.80).
The mirror image — the same collisions, credited to the other man. Dribblers and hold-up forwards spend their evenings being kicked, and it shows up here with the steadiest hit rates on the page. When a fouls-won leader meets a foul-prone opponent, both sides of the mirror are live at once — which is the match-up the model watches for.
| Player | Team | Per 90 | 1+ hit rate | Starts |
|---|---|---|---|---|
| Afonso Moreira forward | Olympique Lyonnais | 2.98 | 100% | 18 |
| Sofiane Boufal midfielder | Le Havre | 2.80 | 92% | 13 |
| Breel Embolo forward | Stade Rennais | 2.79 | 85% | 20 |
| Mohamed Kaba midfielder | Nantes | 2.63 | 73% | 11 |
| Karim Dermane midfielder | Lorient | 2.58 | 100% | 13 |
| Valentín Barco midfielder | RC Strasbourg | 2.53 | 100% | 23 |
| Lucas Gourna-Douath midfielder | Le Havre | 2.47 | 100% | 14 |
| Ilan Kebbal midfielder | Paris FC | 2.46 | 88% | 25 |
| Yann Gboho forward | Toulouse | 2.38 | 86% | 29 |
| Alidu Seidu defender | Stade Rennais | 2.35 | 100% | 12 |
| Lamine Camara midfielder | AS Monaco | 2.33 | 90% | 20 |
| Issa Soumaré midfielder | Le Havre | 2.26 | 91% | 32 |
Tackles — the leaders
In Ligue 1, Bradley Locko (Stade Brestois) leads at 3.66 per 90, ahead of Mamadou Sangare (3.33).
| Player | Team | Per 90 | 1+ hit rate | Starts |
|---|---|---|---|---|
| Bradley Locko defender | Stade Brestois | 3.66 | 100% | 14 |
| Mamadou Sangare midfielder | RC Lens | 3.33 | 96% | 24 |
| Samir El Mourabet midfielder | RC Strasbourg | 3.32 | 91% | 22 |
| Adrien Thomasson midfielder | RC Lens | 3.31 | 93% | 30 |
| Johann Lepenant midfielder | Nantes | 3.27 | 92% | 24 |
| Kamory Doumbia midfielder | Stade Brestois | 3.11 | 95% | 22 |
| Boubacar Traoré midfielder | Metz | 3.04 | 100% | 15 |
| Pierre Lees Melou midfielder | Paris FC | 2.98 | 95% | 22 |
| Przemysław Frankowski midfielder | Stade Rennais | 2.96 | 82% | 11 |
| Marvin Senaya defender | Auxerre | 2.88 | 84% | 19 |
| Koffi Kouao defender | Metz | 2.85 | 93% | 27 |
| Cristian Cásseres Jr. midfielder | Toulouse | 2.81 | 86% | 28 |
Frequently asked
Are these predictions for the new season?
No — they're last season's Ligue 1 rates, shown for players with at least 10 starts. The model only prices a bet once there's a real fixture: an actual opponent, a projected lineup and a live price. Think of this page as the map you study before the season, not the bet slip.
What does hit rate mean here?
The share of a player's starts (60+ minutes) in which the 1+ line would have landed. It's the honesty column: a per-90 rate can flatter a player who piles stats into a few wild games, but a hit rate tells you how often the bet actually wins.
Why is there no cards market on this page?
Deliberately. Cards are the hardest thing we price — in every league we grade, at least one card line comes out no better than the base rate, and the Ligue 1 track record says so — and this page leads with the markets the model demonstrably beats. The referee-driven card analysis lives in the modelling guides instead, where the caveats can travel with it.
Why do the fouls markets reward attention?
Because almost nobody gives them any. Sharp money concentrates on goals and shots, so foul lines are priced coarsely — and on the Ligue 1 track record the 1+ fouls markets beat the baseline by double digits, among the model's strongest results.
Descriptive rates from public match data, shown for context. The model adds shrinkage and opponent adjustments before flagging value against the bookmaker's price as offered (player markets are priced one side only, so it still carries the margin), and grades itself in public on the track record. 18+ — please gamble responsibly.