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Intelligence · Scout desk

The Screener

Every player the intelligence layer tracks, filterable by the numbers it computes. Scores come from event data; estimates stay labeled until measured.

269 of 269 tracked players match — showing the top 100 by sort.
PlayerPosValueOutputG+A /90Avail.AgeTrajectory
N. PazArgentinaMID€185M910.5635 apps100%21improving
Kylian MbappéFranceFWD€129M941.0431 apps95%27→ Stable
Lamine YamalSpainMID€147M810.7134 apps57%18improving
A. GülerReal MadridMID€126M920.5833 apps100%20improving
B. SakaEnglandFWD€120M760.4931 apps79%24↓ Declining
F. WirtzGermanyMID€115M800.3033 apps95%22→ Stable
R. CherkiFranceMID€106M880.8033 apps60%22improving
L. VuškovićCroatiaDEF€95M760.2228 apps99%18improving
E. HaalandNorwayFWD€86.3M891.0635 apps95%25↓ Declining
J. BellinghamEnglandMID€71.7M900.6131 apps88%22↓ Declining
Bruno FernandesPortugalMID€58M940.8835 apps100%31improving
M. BaturinaCroatiaMID€66.2M850.5129 apps99%22→ Stable
Mohamed SalahEgyptFWD€52.4M981.2538 apps100%33→ Stable
PedriSpainMID€63M890.4729 apps94%23improving
J. CurrieOxford UnitedDEF€48.5M920.0639 apps100%23↓ Declining
L. GavranToronto FCGK€35.7M940.0714 apps99%25→ Stable
H. KaneEnglandFWD€45.4M951.2831 apps97%32→ Stable
V. NelssonGalatasarayDEF€40.9M900.0038 apps98%27↓ Declining
J. PantemisPortland TimbersGK€27.3M840.0022 apps95%28improving
J. MusialaGermanyMID€43M840.7025 apps41%22↓ Declining
Vinícius JúniorBrazilMID€41M880.6736 apps95%25→ Stable
M. CarnesecchiItaly U21GK€24.5M950.0037 apps99%25→ Stable
A. DreyerSan DiegoMID€34M961.0337 apps98%27improving
M. RuizTolucaMID€34M830.2430 apps100%25↓ Declining
S. ManéSenegalFWD€28.3M890.8032 apps100%33→ Stable
Ajay MatthewsMillwallFWD€41.1M390.504 apps100%19improving
E. CaprileCagliariGK€20.9M940.0038 apps92%24→ Stable
Kim Seung-GyuSouth KoreaGK€12.5M950.0016 apps100%35→ Stable
L. MartínezArgentinaDEF€28.3M820.0425 apps100%29improving
M. ReteguiAl-Qadisiyah FCFWD€34.3M951.2336 apps96%26improving
N. JacksonSenegalFWD€34.3M770.7823 apps92%24↓ Declining
Son Heung-MinSouth KoreaFWD€26M941.2211 apps90%33↓ Declining
G. BerterameInter MiamiFWD€31.3M820.6922 apps99%27↓ Declining
K. YıldızJuventusFWD€36M800.5136 apps99%20improving
R. HøjlundManchester UnitedFWD€32.8M780.5533 apps93%22→ Stable
D. CoppolaItaly U21DEF€24.5M870.0635 apps98%22→ Stable
D. LainezTigres UANLMID€25.8M880.3937 apps98%25→ Stable
D. RiceEnglandMID€25.8M840.2636 apps96%26→ Stable
A. JungdalDenmark U21GK€15.4M940.0040 apps100%23→ Stable
DaniloBrazilDEF€14.2M920.1737 apps93%34improving
J. KlinsmannUSAGK€15.4M940.0335 apps100%28→ Stable
M. DamsgaardDenmarkMID€23.1M880.3738 apps98%25improving
PaulinhoTolucaFWD€19.2M870.8731 apps100%33↓ Declining
C. EriksenDenmarkMID€15M860.4133 apps99%33improving
F. EspositoItaly U21FWD€24.9M820.6339 apps93%20improving
F. MendySenegalDEF€17.9M830.0727 apps100%24→ Stable
K. GrabaraVfL WolfsburgGK€13.2M940.0036 apps95%26→ Stable
M. SkóraśPoland U21FWD€21.6M840.3132 apps97%25improving
J. CummingOxford UnitedGK€12M920.0046 apps100%26→ Stable
P. HøjbjergDenmarkMID€18.1M760.3032 apps96%30improving
A. OnanaManchester UnitedGK€10.9M840.0034 apps96%29→ Stable
A. GómezColombiaMID€14.7M660.2716 apps95%23improving
J. LukićUniversitatea ClujFWD€16.1M810.7232 apps100%27improving
J. TolkinUSADEF€13.3M750.1333 apps95%23↓ Declining
K. RowlesAustraliaDEF€13.3M790.0031 apps99%27→ Stable
M. KochalskiPolandGK€9.8M840.0017 apps100%25→ Stable
M. PašalićOrlando City SCFWD€16.1M800.5734 apps100%25improving
O. ProvstgaardLazioDEF€14M680.0332 apps100%22↓ Declining
P. DorguManchester UnitedDEF€14.6M700.2022 apps100%21improving
S. Lopes CabralEstrelaDEF€13.3M780.5415 apps96%23improving
S. TanakaJapanMID€14.7M720.2233 apps100%23→ Stable
WevertonBrazilGK€3.5M830.0026 apps100%38↓ Declining
B. De KeersmaeckerOxford UnitedMID€13.4M740.2631 apps98%25improving
F. DimarcoInterMID€13.4M930.7735 apps95%28improving
K. KvaratskheliaParis Saint GermainFWD€14.7M840.7328 apps94%24↓ Declining
M. KeanFiorentinaFWD€14.7M790.7332 apps96%25improving
N. BarellaInterMID€13.4M880.3934 apps96%28improving
Y. En-NesyriFenerbahçeFWD€14.7M871.0834 apps100%28→ Stable
A. ChristensenBarcelonaDEF€11M690.506 apps77%29↓ Declining
Danilo SantosBotafogoMID€12.2M750.7612 apps80%25improving
E. Ben SeghirBayer LeverkusenFWD€15.3M710.4633 apps100%20improving
Findlay CurtisScotlandFWD€16M720.5014 apps100%19improving
H. IgamaneRangersFWD€13.3M780.5934 apps100%23improving
L. MalagónClub AmericaGK€8.1M960.0025 apps100%28→ Stable
M. HelikOxford UnitedDEF€11M770.1243 apps100%30↓ Declining
M. LocatelliJuventusMID€12.2M730.0936 apps98%27improving
P. BillingFC MidtjyllandMID€12.2M720.2320 apps97%29↓ Declining
Wagner PinaTrabzonsporDEF€11M790.2631 apps98%23→ Stable
A. BahBenficaDEF€9.9M900.2429 apps33%28→ Stable
C. RodríguezCruz AzulFWD€12M860.3742 apps98%28→ Stable
D. BallardLeyton OrientFWD€13.8M840.7040 apps100%20improving
Lucas PaquetáBrazilMID€10.9M560.3018 apps96%28→ Stable
SamuFC PortoFWD€13.2M820.8730 apps99%21improving
Victor Mow FroholdtDenmark U19MID€13.1M760.3834 apps100%19improving
G. RaspadoriAtletico MadridFWD€10.6M740.5726 apps100%25↓ Declining
J. AndersenDenmarkDEF€8.7M800.0333 apps96%29↓ Declining
M. de BrienneGaisDEF€8.7M820.2221 apps99%23→ Stable
S. NgezanaSouth AfricaDEF€8.7M790.0427 apps99%28→ Stable
A. CambiasoItaly U21DEF€7.6M810.2336 apps92%25improving
C. NørgaardArsenalMID€7.7M710.2934 apps92%31improving
K. KozłowskiGaziantep FKMID€8.8M690.2731 apps97%22→ Stable
K. TrewinAustraliaDEF€7.6M650.0015 apps97%24↓ Declining
Kerim-Sam AlajbegovićBayer LeverkusenFWD€11.5M680.6024 apps100%18improving
N. ZanioloGalatasarayMID€8.4M840.4432 apps94%26improving
P. SchulteColumbus CrewGK€5.6M830.0027 apps93%24→ Stable
T. OluwayemiLeyton OrientGK€5.9M830.0030 apps100%22improving
V. GuzmánMonterreyDEF€7.6M830.0035 apps92%23→ Stable
A. ŠutoNK Slaven BelupoFWD€8.3M650.6018 apps99%25improving
É. SánchezClub AmericaMID€7.6M730.1442 apps96%26↓ Declining
J. El YamiqAl NajmaDEF€5.2M700.0926 apps100%33improving

Pool: players with a GoalPost Value or Workrate score and a resolved profile. Output and G+A/90 come from this season's stats — mind the appearance sample. Style metrics (Workrate, defensive share) appear as columns when you filter or sort by them; both feed the value model either way.