Eredivisie 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 Eredivisie 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 Eredivisie 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 Eredivisie), Sem Steijn (Feyenoord) tops the shots-on-target watchlist — 1+ shot on target in 100% of starts, and Ayase Ueda (Feyenoord) featured across 3 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 |
|---|---|---|
| Ayase Ueda | Feyenoord | Shots on target, Total shots, Fouls won |
| Ayoni Santos | Sparta Rotterdam | Fouls committed, Tackles |
| Brayann Pereira | NEC Nijmegen | Fouls won, Tackles |
| Brynjólfur Darri Willumsson | FC Groningen | Shots on target, Fouls committed |
| Ismael Saibari | PSV Eindhoven | Shots on target, Total shots |
| Jamiro Monteiro | PEC Zwolle | Fouls won, Tackles |
| Jizz Hornkamp | AZ Alkmaar | Shots on target, Fouls committed |
| Kaj Sierhuis | Fortuna Sittard | Shots on target, Total shots |
| Lequincio Zeefuik | Heracles Almelo | Fouls committed, Fouls won |
| Mohamed Ihattaren | Fortuna Sittard | Shots on target, Total shots |
| Ricardo Pepi | PSV Eindhoven | Shots on target, Total shots |
| Sam Lammers | FC Twente | Shots on target, Total shots |
Shots on target — the leaders
In the Eredivisie, Ricardo Pepi (PSV Eindhoven) leads at 2.01 per 90, ahead of Troy Parrott (1.75).
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 |
|---|---|---|---|---|
| Ricardo Pepi forward | PSV Eindhoven | 2.01 | 93% | 14 |
| Troy Parrott forward | AZ Alkmaar | 1.75 | 83% | 24 |
| Ayase Ueda forward | Feyenoord | 1.63 | 70% | 30 |
| Anthony Descotte midfielder | FC Volendam | 1.61 | 70% | 10 |
| Jizz Hornkamp forward | AZ Alkmaar | 1.60 | 64% | 14 |
| Ismael Saibari midfielder | PSV Eindhoven | 1.59 | 72% | 25 |
| Mohamed Ihattaren midfielder | Fortuna Sittard | 1.57 | 86% | 21 |
| Tjaronn Chery forward | NEC Nijmegen | 1.47 | 61% | 31 |
| Sam Lammers forward | FC Twente | 1.45 | 59% | 17 |
| Brynjólfur Darri Willumsson forward | FC Groningen | 1.42 | 73% | 11 |
| Kaj Sierhuis forward | Fortuna Sittard | 1.40 | 81% | 21 |
| Sem Steijn midfielder | Feyenoord | 1.38 | 100% | 12 |
How SharpXI models shots on target
Total shots — the leaders
In the Eredivisie, Ismael Saibari (PSV Eindhoven) leads at 3.86 per 90, ahead of Ricardo Pepi (3.83).
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 |
|---|---|---|---|---|
| Ismael Saibari midfielder | PSV Eindhoven | 3.86 | 96% | 25 |
| Ricardo Pepi forward | PSV Eindhoven | 3.83 | 93% | 14 |
| Ayase Ueda forward | Feyenoord | 3.62 | 90% | 30 |
| Troy Parrott forward | AZ Alkmaar | 3.59 | 96% | 24 |
| Kaj Sierhuis forward | Fortuna Sittard | 3.56 | 95% | 21 |
| Tjaronn Chery forward | NEC Nijmegen | 3.50 | 97% | 31 |
| Sven Mijnans midfielder | AZ Alkmaar | 3.22 | 92% | 24 |
| Younes Taha forward | FC Groningen | 3.20 | 94% | 32 |
| Mohamed Ihattaren midfielder | Fortuna Sittard | 3.18 | 100% | 21 |
| Sam Lammers forward | FC Twente | 3.18 | 82% | 17 |
| Steven Berghuis forward | AFC Ajax | 3.12 | 80% | 15 |
| Maxence Rivera forward | SC Heerenveen | 3.10 | 91% | 23 |
How SharpXI models total shots
Fouls committed — the leaders
In the Eredivisie, Lequincio Zeefuik (Heracles Almelo) leads at 2.82 per 90, ahead of Dani De Wit (2.24).
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 |
|---|---|---|---|---|
| Lequincio Zeefuik forward | Heracles Almelo | 2.82 | 100% | 11 |
| Dani De Wit midfielder | FC Utrecht | 2.24 | 92% | 26 |
| Thomas Bruns midfielder | Heracles Almelo | 2.16 | 91% | 11 |
| Ricky van Wolfswinkel forward | FC Twente | 2.12 | 82% | 17 |
| Édouard Michut midfielder | Fortuna Sittard | 1.98 | 88% | 17 |
| Jerolldino Bergraaf forward | Excelsior | 1.96 | 82% | 11 |
| Jizz Hornkamp forward | AZ Alkmaar | 1.93 | 86% | 14 |
| Brynjólfur Darri Willumsson forward | FC Groningen | 1.92 | 82% | 11 |
| Ivan Mesík defender | Heracles Almelo | 1.91 | 86% | 29 |
| Leo Greiml defender | NAC Breda | 1.90 | 69% | 13 |
| Ayoni Santos forward | Sparta Rotterdam | 1.89 | 86% | 14 |
| Noah Naujoks midfielder | Excelsior | 1.81 | 89% | 28 |
How SharpXI models fouls committed
Fouls won — the leaders
In the Eredivisie, Joel Ideho (FC Volendam) leads at 2.92 per 90, ahead of Jamiro Monteiro (2.82).
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 |
|---|---|---|---|---|
| Joel Ideho forward | FC Volendam | 2.92 | 100% | 10 |
| Jamiro Monteiro midfielder | PEC Zwolle | 2.82 | 85% | 13 |
| Kaj de Rooij forward | PEC Zwolle | 2.79 | 80% | 20 |
| Édouard Michut midfielder | Fortuna Sittard | 2.66 | 88% | 17 |
| Walid Ould-Chikh forward | Heracles Almelo | 2.52 | 73% | 15 |
| Charles-Andreas Brym forward | NAC Breda | 2.39 | 93% | 15 |
| Miguel Rodríguez forward | FC Utrecht | 2.38 | 85% | 13 |
| Brayann Pereira defender | NEC Nijmegen | 2.31 | 90% | 10 |
| Kasper Dolberg forward | AFC Ajax | 2.26 | 100% | 12 |
| Weslley Patati forward | AZ Alkmaar | 2.24 | 86% | 14 |
| Lequincio Zeefuik forward | Heracles Almelo | 2.14 | 100% | 11 |
| Ayase Ueda forward | Feyenoord | 2.13 | 90% | 30 |
Tackles — the leaders
In the Eredivisie, Jorthy Mokio (AFC Ajax) leads at 3.82 per 90, ahead of Gibson Yah (3.65).
| Player | Team | Per 90 | 1+ hit rate | Starts |
|---|---|---|---|---|
| Jorthy Mokio midfielder | AFC Ajax | 3.82 | 100% | 13 |
| Gibson Yah midfielder | FC Volendam | 3.65 | 89% | 19 |
| Sem Scheperman midfielder | Heracles Almelo | 3.44 | 92% | 12 |
| Bart van Rooij defender | FC Twente | 3.29 | 94% | 33 |
| Alfons Sampsted defender | Go Ahead Eagles | 3.28 | 100% | 10 |
| Peer Koopmeiners midfielder | AZ Alkmaar | 3.28 | 100% | 23 |
| Brayann Pereira defender | NEC Nijmegen | 3.15 | 90% | 10 |
| Ayoni Santos forward | Sparta Rotterdam | 3.14 | 93% | 14 |
| Oussama Targhalline midfielder | Feyenoord | 3.14 | 95% | 20 |
| Nordin Bukala midfielder | FC Volendam | 3.08 | 90% | 20 |
| Jordan Bos defender | Feyenoord | 3.06 | 100% | 21 |
| Jamiro Monteiro midfielder | PEC Zwolle | 3.03 | 92% | 13 |
Frequently asked
Are these predictions for the new season?
No — they're last season's Eredivisie 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 Eredivisie 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 Eredivisie 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.