PER90My betsAccount

Premier League · England

Nottingham ForestvLeeds United

The City Groundlineups not announced

Referee

Not appointed

0 matches on record

Fouls per game

League average

22.6

fouls per match, both teams

Value

No edges published on this fixture. An edge is published only when a bookmaker's price beats the model's fair price by that market's full bar — most fixtures never produce one. The value board explains every gate a candidate has to clear.

What these numbers are

Not tips and not prices. Each row is the model's expected count for one player in this match — how many fouls, tackles or shots it thinks he records — plus the full spread of outcomes around it. Nothing here has been compared to a bookmaker.

  1. Step 1

    His own record

    Every completed match in the dataset, as a rate per 90 minutes. The n column is how many matches that rests on.

  2. Step 2

    Pulled toward his position

    A thin record gets pulled hard toward other players in his position, in his league — a goalkeeper toward goalkeepers, not toward the outfielders around him. How hard is fitted per market, not chosen: tackles pull about four times harder than shots on target.

  3. Step 3

    This fixture's conditions

    How much of the stat the opponent concedes, what the referee's matches look like, and home or away. This is where a projection stops being a season average.

  4. Step 4

    Scaled to expected minutes

    A rate becomes a count only once you say how long he plays. 60 minutes carries two-thirds the exposure of 90, and the distribution is built at that exposure.

How to read each column
Model /90
The model's rate for this match with the minutes taken back out — steps 1 to 3 already applied. It moves with the opponent and the referee, so it is not his raw career rate; the builder shows career and model rates side by side.
Exp. mins
Minutes the model expects. Confirmed means the lineup is out; provisional means it is guessing from his start rate, and is the widest of the three.
Projected
The expected count in this match, at those minutes. This is the number a line is set against.
Over 1.5, etc.
Read straight off the distribution beside it, not off how often he has beaten that line before. It answers what the model thinks, not what has happened.
n
Matches behind his own rate. Under 30 it turns amber: the projection is mostly his position group speaking, and §6.3 will not publish an edge on it.
Distribution
The whole spread, not just the average. The dashed amber cut is the line; jade bars beat it. An expected 1.8 fouls made of 2 every week and an expected 1.8 made of a 0 and a 5 are different bets, and this is where you see which one you have.

Counts are modelled as negative binomial rather than Poisson, because fouls and tackles are overdispersed and a Poisson would systematically underprice the tails — which is exactly where over bets live. Every market on this page cleared its calibration gate before it was allowed to produce a projection: when the model says 60%, it lands within a point or so of 60% out of sample.

Fouls v20260811-1858 · Tackles v20260811-1858 · Shots v20260811-1858 · Shots on target v20260811-1905 · Fouls won v20260811-1858 · Cards v20260811-1905 · Saves v20260812-1340

Model projections

Fouls41 playersHighest: Ethan Ampadu, 1.15 expectedshow

What drives it Who referees the match. A strict official lifts every player on the pitch, which is the part most books price off a season average. See what has actually happened.

  • Ethan Ampadu

    MID · Leeds United

    provisional
    Mins
    85
    Proj.
    1.15
    O 1.5
    32%
    Model /90
    1.22
    034%
    134%
    220%
    38%
    43%
    51%
    6+0%
  • Anton Stach

    MID · Leeds United

    provisional
    Mins
    82
    Proj.
    1.15
    O 1.5
    32%
    Model /90
    1.26
    034%
    135%
    220%
    38%
    43%
    51%
    6+0%
  • Dominic Calvert-Lewin

    FWD · Leeds United

    provisional
    Mins
    78
    Proj.
    1.14
    O 1.5
    32%
    Model /90
    1.32
    035%
    133%
    219%
    38%
    43%
    51%
    6+0%
  • Ibrahim Sangaré

    MID · Nottingham Forest

    provisional
    Mins
    65
    Proj.
    1.05
    O 1.5
    29%
    Model /90
    1.45
    041%
    130%
    217%
    38%
    43%
    51%
    6+0%
  • Nicolás Martín Domínguez

    MID · Nottingham Forest

    provisional
    Mins
    52
    Proj.
    1.04
    O 1.5
    28%
    Model /90
    1.80
    041%
    131%
    217%
    37%
    43%
    51%
    6+0%
  • Morgan Gibbs-White

    MID · Nottingham Forest

    provisional
    Mins
    84
    Proj.
    1.03
    O 1.5
    27%
    Model /90
    1.11
    037%
    135%
    218%
    37%
    42%
    51%
    6+0%
  • Sean Longstaff

    MID · Leeds United

    provisional
    Mins
    44
    Proj.
    1.01
    O 1.5
    26%
    Model /90
    2.06
    049%
    124%
    213%
    37%
    44%
    52%
    6+1%
  • Igor Jesus Maciel da Cruz

    FWD · Nottingham Forest

    provisional
    Mins
    63
    Proj.
    0.96
    O 1.5
    25%
    Model /90
    1.38
    042%
    132%
    216%
    36%
    42%
    51%
    6+0%
  • Ao Tanaka

    MID · Leeds United

    provisional
    Mins
    66
    Proj.
    0.95
    O 1.5
    25%
    Model /90
    1.31
    044%
    131%
    216%
    37%
    42%
    51%
    6+0%
  • Brenden Aaronson

    MID · Leeds United

    provisional
    Mins
    73
    Proj.
    0.95
    O 1.5
    25%
    Model /90
    1.18
    041%
    134%
    217%
    36%
    42%
    50%
    6+0%
  • Ilia Gruev

    MID · Leeds United

    provisional
    Mins
    66
    Proj.
    0.94
    O 1.5
    25%
    Model /90
    1.29
    044%
    131%
    216%
    36%
    42%
    51%
    6+0%
  • Chris Wood

    FWD · Nottingham Forest

    provisional
    Mins
    76
    Proj.
    0.94
    O 1.5
    25%
    Model /90
    1.11
    041%
    134%
    216%
    36%
    42%
    50%
    6+0%
  • Joël Piroe

    FWD · Leeds United

    provisional
    Mins
    54
    Proj.
    0.88
    O 1.5
    23%
    Model /90
    1.46
    050%
    127%
    214%
    36%
    42%
    51%
    6+0%
  • Jayden Bogle

    DEF · Leeds United

    provisional
    Mins
    85
    Proj.
    0.84
    O 1.5
    21%
    Model /90
    0.89
    044%
    135%
    215%
    35%
    41%
    5+0%
  • Ryan Yates

    MID · Nottingham Forest

    provisional
    Mins
    45
    Proj.
    0.84
    O 1.5
    21%
    Model /90
    1.69
    050%
    129%
    213%
    35%
    42%
    51%
    6+0%
  • Noah Okafor

    FWD · Leeds United

    provisional
    Mins
    56
    Proj.
    0.83
    O 1.5
    21%
    Model /90
    1.33
    048%
    131%
    214%
    35%
    42%
    50%
    6+0%
  • Omari Giraud-Hutchinson

    FWD · Nottingham Forest

    provisional
    Mins
    54
    Proj.
    0.81
    O 1.5
    20%
    Model /90
    1.34
    049%
    130%
    213%
    35%
    42%
    50%
    6+0%
  • Dan Ndoye

    FWD · Nottingham Forest

    provisional
    Mins
    49
    Proj.
    0.80
    O 1.5
    21%
    Model /90
    1.48
    050%
    129%
    213%
    35%
    42%
    50%
    6+0%
  • Callum Hudson-Odoi

    FWD · Nottingham Forest

    provisional
    Mins
    66
    Proj.
    0.80
    O 1.5
    20%
    Model /90
    1.08
    048%
    133%
    214%
    34%
    41%
    5+0%
  • Gabriel Gudmundsson

    DEF · Leeds United

    provisional
    Mins
    83
    Proj.
    0.78
    O 1.5
    19%
    Model /90
    0.85
    047%
    134%
    214%
    34%
    41%
    5+0%

20 of 41 players shown, ranked by projection.

Tackles41 playersHighest: Nicolás Martín Domínguez, 2.95 expectedshow

What drives it Possession share. A tackle count depends far more on how much of the match is played at your own end than on a player’s own form. See what has actually happened.

  • Nicolás Martín Domínguez

    MID · Nottingham Forest

    provisional
    Mins
    52
    Proj.
    2.95
    O 1.5
    69%
    Model /90
    5.13
    013%
    118%
    217%
    316%
    413%
    510%
    6+13%
  • Anton Stach

    MID · Leeds United

    provisional
    Mins
    82
    Proj.
    2.04
    O 1.5
    60%
    Model /90
    2.23
    014%
    126%
    226%
    318%
    49%
    54%
    6+2%
  • Ethan Ampadu

    MID · Leeds United

    provisional
    Mins
    85
    Proj.
    1.96
    O 1.5
    58%
    Model /90
    2.08
    016%
    127%
    226%
    317%
    49%
    54%
    6+2%
  • Ibrahim Sangaré

    MID · Nottingham Forest

    provisional
    Mins
    65
    Proj.
    1.85
    O 1.5
    53%
    Model /90
    2.56
    024%
    124%
    222%
    316%
    49%
    54%
    6+2%
  • Neco Williams

    DEF · Nottingham Forest

    provisional
    Mins
    80
    Proj.
    1.85
    O 1.5
    54%
    Model /90
    2.07
    019%
    127%
    225%
    316%
    48%
    53%
    6+2%
  • Ao Tanaka

    MID · Leeds United

    provisional
    Mins
    66
    Proj.
    1.77
    O 1.5
    50%
    Model /90
    2.43
    025%
    125%
    221%
    315%
    48%
    54%
    6+2%
  • Brenden Aaronson

    MID · Leeds United

    provisional
    Mins
    73
    Proj.
    1.71
    O 1.5
    50%
    Model /90
    2.11
    021%
    129%
    224%
    315%
    47%
    53%
    6+1%
  • Jayden Bogle

    DEF · Leeds United

    provisional
    Mins
    85
    Proj.
    1.67
    O 1.5
    49%
    Model /90
    1.76
    020%
    131%
    226%
    314%
    46%
    52%
    6+1%
  • Gabriel Gudmundsson

    DEF · Leeds United

    provisional
    Mins
    83
    Proj.
    1.60
    O 1.5
    47%
    Model /90
    1.75
    021%
    132%
    225%
    314%
    46%
    52%
    6+1%
  • Morgan Gibbs-White

    MID · Nottingham Forest

    provisional
    Mins
    84
    Proj.
    1.59
    O 1.5
    47%
    Model /90
    1.71
    021%
    132%
    225%
    314%
    46%
    52%
    6+1%
  • Ilia Gruev

    MID · Leeds United

    provisional
    Mins
    66
    Proj.
    1.57
    O 1.5
    45%
    Model /90
    2.14
    027%
    128%
    222%
    313%
    46%
    53%
    6+1%
  • Temitayo Olufisayo Olaoluwa Aina

    DEF · Nottingham Forest

    provisional
    Mins
    87
    Proj.
    1.55
    O 1.5
    46%
    Model /90
    1.61
    022%
    133%
    225%
    313%
    45%
    52%
    6+1%
  • Murillo Santiago Costa dos Santos

    DEF · Nottingham Forest

    provisional
    Mins
    87
    Proj.
    1.49
    O 1.5
    44%
    Model /90
    1.54
    023%
    133%
    225%
    312%
    45%
    51%
    6+0%
  • Nicolò Savona

    DEF · Nottingham Forest

    provisional
    Mins
    73
    Proj.
    1.45
    O 1.5
    42%
    Model /90
    1.78
    027%
    131%
    223%
    312%
    45%
    52%
    6+1%
  • Nikola Milenković

    DEF · Nottingham Forest

    provisional
    Mins
    89
    Proj.
    1.34
    O 1.5
    39%
    Model /90
    1.35
    026%
    135%
    223%
    311%
    44%
    51%
    6+0%
  • Jaka Bijol

    DEF · Leeds United

    provisional
    Mins
    76
    Proj.
    1.33
    O 1.5
    38%
    Model /90
    1.58
    029%
    132%
    222%
    311%
    44%
    51%
    6+0%
  • James Justin

    DEF · Leeds United

    provisional
    Mins
    65
    Proj.
    1.29
    O 1.5
    37%
    Model /90
    1.77
    036%
    127%
    219%
    311%
    45%
    52%
    6+1%
  • Joe Rodon

    DEF · Leeds United

    provisional
    Mins
    88
    Proj.
    1.24
    O 1.5
    35%
    Model /90
    1.28
    029%
    135%
    222%
    39%
    43%
    51%
    6+0%
  • Felipe Rodrigues

    DEF · Nottingham Forest

    provisional
    Mins
    48
    Proj.
    1.24
    O 1.5
    33%
    Model /90
    2.34
    040%
    127%
    215%
    39%
    45%
    52%
    6+1%
  • Sean Longstaff

    MID · Leeds United

    provisional
    Mins
    44
    Proj.
    1.23
    O 1.5
    33%
    Model /90
    2.51
    043%
    124%
    214%
    39%
    45%
    53%
    6+2%

20 of 41 players shown, ranked by projection.

Shots41 playersHighest: Dominic Calvert-Lewin, 1.83 expectedshow

What drives it The player’s own shot rate, shrunk toward others in his position, then adjusted for how many shots the opponent concedes. See what has actually happened.

  • Dominic Calvert-Lewin

    FWD · Leeds United

    provisional
    Mins
    78
    Proj.
    1.83
    O 1.5
    51%
    Model /90
    2.11
    023%
    127%
    222%
    314%
    48%
    54%
    6+3%
  • Chris Wood

    FWD · Nottingham Forest

    provisional
    Mins
    76
    Proj.
    1.76
    O 1.5
    49%
    Model /90
    2.09
    023%
    128%
    222%
    314%
    47%
    53%
    6+2%
  • Igor Jesus Maciel da Cruz

    FWD · Nottingham Forest

    provisional
    Mins
    63
    Proj.
    1.68
    O 1.5
    46%
    Model /90
    2.42
    026%
    128%
    221%
    313%
    47%
    53%
    6+2%
  • Daniel James

    FWD · Leeds United

    provisional
    Mins
    58
    Proj.
    1.61
    O 1.5
    43%
    Model /90
    2.52
    032%
    125%
    218%
    312%
    47%
    54%
    6+3%
  • Joël Piroe

    FWD · Leeds United

    provisional
    Mins
    54
    Proj.
    1.54
    O 1.5
    40%
    Model /90
    2.56
    036%
    124%
    216%
    311%
    47%
    54%
    6+3%
  • Callum Hudson-Odoi

    FWD · Nottingham Forest

    provisional
    Mins
    66
    Proj.
    1.48
    O 1.5
    41%
    Model /90
    2.01
    029%
    130%
    220%
    311%
    45%
    52%
    6+1%
  • Omari Giraud-Hutchinson

    FWD · Nottingham Forest

    provisional
    Mins
    54
    Proj.
    1.38
    O 1.5
    37%
    Model /90
    2.28
    034%
    129%
    218%
    310%
    45%
    52%
    6+2%
  • Noah Okafor

    FWD · Leeds United

    provisional
    Mins
    56
    Proj.
    1.34
    O 1.5
    37%
    Model /90
    2.16
    034%
    129%
    218%
    310%
    45%
    52%
    6+1%
  • Dan Ndoye

    FWD · Nottingham Forest

    provisional
    Mins
    49
    Proj.
    1.24
    O 1.5
    33%
    Model /90
    2.28
    039%
    128%
    216%
    39%
    44%
    52%
    6+1%
  • Morgan Gibbs-White

    MID · Nottingham Forest

    provisional
    Mins
    84
    Proj.
    1.22
    O 1.5
    34%
    Model /90
    1.31
    033%
    134%
    220%
    39%
    43%
    51%
    6+0%
  • Lukas Nmecha

    FWD · Leeds United

    provisional
    Mins
    35
    Proj.
    1.16
    O 1.5
    29%
    Model /90
    3.02
    043%
    128%
    214%
    37%
    44%
    52%
    6+2%
  • Degnand Wilfried Gnonto

    FWD · Leeds United

    provisional
    Mins
    43
    Proj.
    1.14
    O 1.5
    29%
    Model /90
    2.41
    044%
    126%
    214%
    38%
    44%
    52%
    6+1%
  • Anton Stach

    MID · Leeds United

    provisional
    Mins
    82
    Proj.
    1.09
    O 1.5
    29%
    Model /90
    1.19
    037%
    134%
    218%
    37%
    43%
    51%
    6+0%
  • Dilane Bakwa

    FWD · Nottingham Forest

    provisional
    Mins
    40
    Proj.
    1.07
    O 1.5
    28%
    Model /90
    2.44
    042%
    130%
    215%
    37%
    43%
    51%
    6+1%
  • Brenden Aaronson

    MID · Leeds United

    provisional
    Mins
    73
    Proj.
    1.01
    O 1.5
    27%
    Model /90
    1.25
    040%
    133%
    217%
    37%
    42%
    51%
    6+0%
  • Ethan Ampadu

    MID · Leeds United

    provisional
    Mins
    85
    Proj.
    0.91
    O 1.5
    23%
    Model /90
    0.97
    043%
    134%
    216%
    36%
    42%
    50%
    6+0%
  • provisional
    Mins
    33
    Proj.
    0.91
    O 1.5
    22%
    Model /90
    2.49
    053%
    125%
    211%
    35%
    43%
    52%
    6+1%
  • Largie Ramazani

    FWD · Leeds United

    provisional
    Mins
    28
    Proj.
    0.86
    O 1.5
    20%
    Model /90
    2.79
    053%
    127%
    211%
    35%
    42%
    51%
    6+1%
  • Ilia Gruev

    MID · Leeds United

    provisional
    Mins
    66
    Proj.
    0.79
    O 1.5
    20%
    Model /90
    1.09
    050%
    130%
    213%
    35%
    41%
    50%
    6+0%
  • Ibrahim Sangaré

    MID · Nottingham Forest

    provisional
    Mins
    65
    Proj.
    0.79
    O 1.5
    20%
    Model /90
    1.10
    050%
    130%
    213%
    35%
    41%
    50%
    6+0%

20 of 41 players shown, ranked by projection.

Shots on target39 playersHighest: Chris Wood, 0.82 expectedshow

What drives it Shot volume first, conversion second — literally: the projection is the shots model thinned by the player’s own on-target rate, so a high-volume low-accuracy shooter and a sniper price differently at the same shot count. See what has actually happened.

  • Chris Wood

    FWD · Nottingham Forest

    provisional
    Mins
    76
    Proj.
    0.82
    O 0.5
    53%
    Model /90
    0.97
    047%
    133%
    214%
    35%
    41%
    5+0%
  • Dominic Calvert-Lewin

    FWD · Leeds United

    provisional
    Mins
    78
    Proj.
    0.80
    O 0.5
    52%
    Model /90
    0.93
    048%
    132%
    214%
    35%
    41%
    5+0%
  • Callum Hudson-Odoi

    FWD · Nottingham Forest

    provisional
    Mins
    66
    Proj.
    0.60
    O 0.5
    42%
    Model /90
    0.81
    058%
    129%
    210%
    33%
    41%
    5+0%
  • Omari Giraud-Hutchinson

    FWD · Nottingham Forest

    provisional
    Mins
    54
    Proj.
    0.59
    O 0.5
    41%
    Model /90
    0.98
    059%
    128%
    210%
    33%
    41%
    5+0%
  • Joël Piroe

    FWD · Leeds United

    provisional
    Mins
    54
    Proj.
    0.59
    O 0.5
    39%
    Model /90
    0.99
    061%
    125%
    210%
    33%
    41%
    5+0%
  • Igor Jesus Maciel da Cruz

    FWD · Nottingham Forest

    provisional
    Mins
    63
    Proj.
    0.58
    O 0.5
    42%
    Model /90
    0.84
    058%
    129%
    29%
    32%
    41%
    5+0%
  • Daniel James

    FWD · Leeds United

    provisional
    Mins
    58
    Proj.
    0.58
    O 0.5
    40%
    Model /90
    0.90
    060%
    127%
    29%
    33%
    41%
    5+0%
  • Noah Okafor

    FWD · Leeds United

    provisional
    Mins
    56
    Proj.
    0.56
    O 0.5
    40%
    Model /90
    0.89
    060%
    128%
    29%
    32%
    41%
    5+0%
  • Lukas Nmecha

    FWD · Leeds United

    provisional
    Mins
    35
    Proj.
    0.53
    O 0.5
    36%
    Model /90
    1.38
    064%
    124%
    28%
    33%
    41%
    5+0%
  • Dan Ndoye

    FWD · Nottingham Forest

    provisional
    Mins
    49
    Proj.
    0.45
    O 0.5
    33%
    Model /90
    0.83
    067%
    124%
    27%
    32%
    4+0%
  • Morgan Gibbs-White

    MID · Nottingham Forest

    provisional
    Mins
    84
    Proj.
    0.44
    O 0.5
    35%
    Model /90
    0.47
    065%
    127%
    26%
    31%
    4+0%
  • Dilane Bakwa

    FWD · Nottingham Forest

    provisional
    Mins
    40
    Proj.
    0.42
    O 0.5
    31%
    Model /90
    0.95
    069%
    124%
    26%
    31%
    4+0%
  • Degnand Wilfried Gnonto

    FWD · Leeds United

    provisional
    Mins
    43
    Proj.
    0.39
    O 0.5
    29%
    Model /90
    0.82
    071%
    121%
    26%
    31%
    4+0%
  • provisional
    Mins
    33
    Proj.
    0.37
    O 0.5
    27%
    Model /90
    1.01
    073%
    119%
    25%
    32%
    40%
    5+0%
  • Largie Ramazani

    FWD · Leeds United

    provisional
    Mins
    28
    Proj.
    0.36
    O 0.5
    27%
    Model /90
    1.18
    073%
    120%
    25%
    31%
    40%
    5+0%
  • Brenden Aaronson

    MID · Leeds United

    provisional
    Mins
    73
    Proj.
    0.34
    O 0.5
    28%
    Model /90
    0.42
    072%
    123%
    24%
    3+1%
  • Taiwo Michael Awoniyi

    FWD · Nottingham Forest

    provisional
    Mins
    21
    Proj.
    0.31
    O 0.5
    24%
    Model /90
    1.33
    076%
    119%
    24%
    31%
    4+0%
  • Anton Stach

    MID · Leeds United

    provisional
    Mins
    82
    Proj.
    0.31
    O 0.5
    26%
    Model /90
    0.34
    074%
    122%
    24%
    3+1%
  • Ibrahim Sangaré

    MID · Nottingham Forest

    provisional
    Mins
    65
    Proj.
    0.26
    O 0.5
    22%
    Model /90
    0.36
    078%
    119%
    23%
    3+0%
  • Ethan Ampadu

    MID · Leeds United

    provisional
    Mins
    85
    Proj.
    0.24
    O 0.5
    21%
    Model /90
    0.26
    079%
    118%
    23%
    3+0%

20 of 39 players shown, ranked by projection.

Fouls won41 playersHighest: Brenden Aaronson, 1.06 expectedshow

What drives it How much a player runs at defenders. Dribble volume drives this far more than the referee does. See what has actually happened.

  • Brenden Aaronson

    MID · Leeds United

    provisional
    Mins
    73
    Proj.
    1.06
    O 1.5
    28%
    Model /90
    1.31
    039%
    132%
    217%
    37%
    43%
    51%
    6+0%
  • Dominic Calvert-Lewin

    FWD · Leeds United

    provisional
    Mins
    78
    Proj.
    1.05
    O 1.5
    28%
    Model /90
    1.21
    040%
    132%
    217%
    37%
    43%
    51%
    6+0%
  • Morgan Gibbs-White

    MID · Nottingham Forest

    provisional
    Mins
    84
    Proj.
    1.04
    O 1.5
    28%
    Model /90
    1.12
    038%
    134%
    218%
    37%
    42%
    51%
    6+0%
  • Callum Hudson-Odoi

    FWD · Nottingham Forest

    provisional
    Mins
    66
    Proj.
    1.04
    O 1.5
    28%
    Model /90
    1.40
    040%
    132%
    217%
    37%
    43%
    51%
    6+0%
  • Ethan Ampadu

    MID · Leeds United

    provisional
    Mins
    85
    Proj.
    0.98
    O 1.5
    26%
    Model /90
    1.05
    041%
    133%
    217%
    36%
    42%
    51%
    6+0%
  • Anton Stach

    MID · Leeds United

    provisional
    Mins
    82
    Proj.
    0.96
    O 1.5
    25%
    Model /90
    1.06
    041%
    134%
    216%
    36%
    42%
    51%
    6+0%
  • Dan Ndoye

    FWD · Nottingham Forest

    provisional
    Mins
    49
    Proj.
    0.95
    O 1.5
    25%
    Model /90
    1.74
    047%
    128%
    214%
    37%
    43%
    51%
    6+0%
  • Igor Jesus Maciel da Cruz

    FWD · Nottingham Forest

    provisional
    Mins
    63
    Proj.
    0.94
    O 1.5
    25%
    Model /90
    1.36
    044%
    131%
    215%
    36%
    42%
    51%
    6+0%
  • Chris Wood

    FWD · Nottingham Forest

    provisional
    Mins
    76
    Proj.
    0.93
    O 1.5
    24%
    Model /90
    1.10
    043%
    133%
    216%
    36%
    42%
    51%
    6+0%
  • Ilia Gruev

    MID · Leeds United

    provisional
    Mins
    66
    Proj.
    0.83
    O 1.5
    21%
    Model /90
    1.14
    049%
    130%
    214%
    35%
    42%
    50%
    6+0%
  • Daniel James

    FWD · Leeds United

    provisional
    Mins
    58
    Proj.
    0.82
    O 1.5
    21%
    Model /90
    1.29
    051%
    128%
    213%
    35%
    42%
    51%
    6+0%
  • Neco Williams

    DEF · Nottingham Forest

    provisional
    Mins
    80
    Proj.
    0.81
    O 1.5
    20%
    Model /90
    0.91
    048%
    132%
    214%
    35%
    41%
    5+0%
  • Omari Giraud-Hutchinson

    FWD · Nottingham Forest

    provisional
    Mins
    54
    Proj.
    0.81
    O 1.5
    20%
    Model /90
    1.34
    050%
    130%
    213%
    35%
    42%
    51%
    6+0%
  • Degnand Wilfried Gnonto

    FWD · Leeds United

    provisional
    Mins
    43
    Proj.
    0.80
    O 1.5
    20%
    Model /90
    1.69
    054%
    126%
    212%
    35%
    42%
    51%
    6+0%
  • Ibrahim Sangaré

    MID · Nottingham Forest

    provisional
    Mins
    65
    Proj.
    0.80
    O 1.5
    20%
    Model /90
    1.10
    050%
    130%
    213%
    35%
    41%
    50%
    6+0%
  • Gabriel Gudmundsson

    DEF · Leeds United

    provisional
    Mins
    83
    Proj.
    0.78
    O 1.5
    19%
    Model /90
    0.85
    048%
    133%
    213%
    34%
    41%
    5+0%
  • Jayden Bogle

    DEF · Leeds United

    provisional
    Mins
    85
    Proj.
    0.76
    O 1.5
    18%
    Model /90
    0.80
    049%
    133%
    213%
    34%
    41%
    5+0%
  • Ryan Yates

    MID · Nottingham Forest

    provisional
    Mins
    45
    Proj.
    0.74
    O 1.5
    18%
    Model /90
    1.50
    054%
    128%
    211%
    34%
    42%
    51%
    6+0%
  • Noah Okafor

    FWD · Leeds United

    provisional
    Mins
    56
    Proj.
    0.74
    O 1.5
    18%
    Model /90
    1.18
    052%
    130%
    212%
    34%
    41%
    50%
    6+0%
  • Ao Tanaka

    MID · Leeds United

    provisional
    Mins
    66
    Proj.
    0.74
    O 1.5
    18%
    Model /90
    1.01
    053%
    129%
    212%
    34%
    41%
    50%
    6+0%

20 of 41 players shown, ranked by projection.

Cards41 playersHighest: Ethan Ampadu, 0.21 expectedshow

Known defect Prices ANY card — yellow or straight red — matching how books settle "to be shown a card" (D-048). The trends column alongside counts yellows only.

What drives it Fouls first, then how readily the referee reaches for a card. Two officials averaging four cards a match can do it for opposite reasons. See what has actually happened.

  • Ethan Ampadu

    MID · Leeds United

    provisional
    Mins
    85
    Proj.
    0.21
    O 0.5
    18%
    Model /90
    0.22
    082%
    116%
    22%
    3+0%
  • Nicolás Martín Domínguez

    MID · Nottingham Forest

    provisional
    Mins
    52
    Proj.
    0.21
    O 0.5
    18%
    Model /90
    0.36
    082%
    116%
    22%
    3+0%
  • Anton Stach

    MID · Leeds United

    provisional
    Mins
    82
    Proj.
    0.19
    O 0.5
    17%
    Model /90
    0.21
    083%
    115%
    22%
    3+0%
  • Morgan Gibbs-White

    MID · Nottingham Forest

    provisional
    Mins
    84
    Proj.
    0.19
    O 0.5
    17%
    Model /90
    0.20
    083%
    115%
    22%
    3+0%
  • Sean Longstaff

    MID · Leeds United

    provisional
    Mins
    44
    Proj.
    0.18
    O 0.5
    16%
    Model /90
    0.38
    084%
    113%
    22%
    3+0%
  • Ibrahim Sangaré

    MID · Nottingham Forest

    provisional
    Mins
    65
    Proj.
    0.18
    O 0.5
    16%
    Model /90
    0.25
    084%
    114%
    22%
    3+0%
  • Felipe Rodrigues

    DEF · Nottingham Forest

    provisional
    Mins
    48
    Proj.
    0.18
    O 0.5
    16%
    Model /90
    0.34
    084%
    113%
    22%
    3+0%
  • Jayden Bogle

    DEF · Leeds United

    provisional
    Mins
    85
    Proj.
    0.17
    O 0.5
    16%
    Model /90
    0.18
    084%
    114%
    2+1%
  • Murillo Santiago Costa dos Santos

    DEF · Nottingham Forest

    provisional
    Mins
    87
    Proj.
    0.17
    O 0.5
    16%
    Model /90
    0.18
    084%
    114%
    2+1%
  • Gabriel Gudmundsson

    DEF · Leeds United

    provisional
    Mins
    83
    Proj.
    0.17
    O 0.5
    15%
    Model /90
    0.19
    085%
    114%
    2+1%
  • Temitayo Olufisayo Olaoluwa Aina

    DEF · Nottingham Forest

    provisional
    Mins
    87
    Proj.
    0.17
    O 0.5
    15%
    Model /90
    0.17
    085%
    114%
    2+1%
  • Neco Williams

    DEF · Nottingham Forest

    provisional
    Mins
    80
    Proj.
    0.16
    O 0.5
    15%
    Model /90
    0.18
    085%
    114%
    2+1%
  • Jaka Bijol

    DEF · Leeds United

    provisional
    Mins
    76
    Proj.
    0.16
    O 0.5
    15%
    Model /90
    0.19
    085%
    114%
    2+1%
  • Ao Tanaka

    MID · Leeds United

    provisional
    Mins
    66
    Proj.
    0.16
    O 0.5
    15%
    Model /90
    0.22
    085%
    113%
    21%
    3+0%
  • Nicolò Savona

    DEF · Nottingham Forest

    provisional
    Mins
    73
    Proj.
    0.16
    O 0.5
    15%
    Model /90
    0.20
    085%
    113%
    2+1%
  • Nikola Milenković

    DEF · Nottingham Forest

    provisional
    Mins
    89
    Proj.
    0.16
    O 0.5
    15%
    Model /90
    0.16
    085%
    113%
    2+1%
  • Ilia Gruev

    MID · Leeds United

    provisional
    Mins
    66
    Proj.
    0.16
    O 0.5
    14%
    Model /90
    0.22
    086%
    113%
    2+1%
  • Ryan Yates

    MID · Nottingham Forest

    provisional
    Mins
    45
    Proj.
    0.16
    O 0.5
    14%
    Model /90
    0.32
    086%
    113%
    21%
    3+0%
  • Brenden Aaronson

    MID · Leeds United

    provisional
    Mins
    73
    Proj.
    0.14
    O 0.5
    13%
    Model /90
    0.18
    087%
    112%
    2+1%
  • James Justin

    DEF · Leeds United

    provisional
    Mins
    65
    Proj.
    0.14
    O 0.5
    13%
    Model /90
    0.20
    087%
    112%
    2+1%

20 of 41 players shown, ranked by projection.

Saves41 playersHighest: Lucas Estella Perri, 3.05 expectedshow

What drives it Opponent shot volume. A keeper’s own record carries so little that this market shrinks harder than any other on the board. See what has actually happened.

  • Lucas Estella Perri

    GK · Leeds United

    provisional
    Mins
    90
    Proj.
    3.05
    O 2.5
    56%
    Model /90
    3.05
    07%
    116%
    221%
    320%
    415%
    510%
    6+11%
  • Matz Sels

    GK · Nottingham Forest

    provisional
    Mins
    88
    Proj.
    2.73
    O 2.5
    50%
    Model /90
    2.79
    09%
    119%
    222%
    320%
    414%
    58%
    6+8%
  • Jaka Bijol

    DEF · Leeds United

    provisional
    Mins
    76
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Sebastiaan Bornauw

    DEF · Leeds United

    provisional
    Mins
    37
    Proj.
    0.00
    O 2.5
    Model /90
    0.01
    0100%
    1+0%
  • Joe Rodon

    DEF · Leeds United

    provisional
    Mins
    88
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Murillo Santiago Costa dos Santos

    DEF · Nottingham Forest

    provisional
    Mins
    87
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Nikola Milenković

    DEF · Nottingham Forest

    provisional
    Mins
    89
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Felipe Rodrigues

    DEF · Nottingham Forest

    provisional
    Mins
    48
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Jayden Bogle

    DEF · Leeds United

    provisional
    Mins
    85
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Ethan Ampadu

    MID · Leeds United

    provisional
    Mins
    85
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Anton Stach

    MID · Leeds United

    provisional
    Mins
    82
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Gabriel Gudmundsson

    DEF · Leeds United

    provisional
    Mins
    83
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Dominic Calvert-Lewin

    FWD · Leeds United

    provisional
    Mins
    78
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Brenden Aaronson

    MID · Leeds United

    provisional
    Mins
    73
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • James Justin

    DEF · Leeds United

    provisional
    Mins
    65
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Ao Tanaka

    MID · Leeds United

    provisional
    Mins
    66
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Ilia Gruev

    MID · Leeds United

    provisional
    Mins
    66
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Temitayo Olufisayo Olaoluwa Aina

    DEF · Nottingham Forest

    provisional
    Mins
    87
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Morgan Gibbs-White

    MID · Nottingham Forest

    provisional
    Mins
    84
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Neco Williams

    DEF · Nottingham Forest

    provisional
    Mins
    80
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%

20 of 41 players shown, ranked by projection.