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Player-market outlook · 25/26

Ligue 1 player-market outlook — shots, fouls 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 and fouls, 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.

PlayerTeamLeads these markets
Ahmadou Bamba Dieng Lorient Shots on target, Total shots
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.

PlayerTeamPer 90 1+ hit rateStarts
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.

PlayerTeamPer 90 1+ hit rateStarts
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.

PlayerTeamPer 90 1+ hit rateStarts
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.

PlayerTeamPer 90 1+ hit rateStarts
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

How SharpXI models fouls won →

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 cover, 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, opponent adjustments and de-vigging before flagging value, and grades itself in public on the track record. 18+ — please gamble responsibly.