PER90My betsAccount

Bundesliga · Germany

FC Bayern MünchenvVfB Stuttgart

Allianz Arenalineups 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

Fouls43 playersHighest: Luis Fernando Díaz Marulanda, 1.08 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.

  • Luis Fernando Díaz Marulanda

    FWD · FC Bayern München

    provisional
    Mins
    78
    Proj.
    1.08
    O 1.5
    29%
    Model /90
    1.25
    037%
    134%
    218%
    37%
    42%
    51%
    6+0%
  • Deniz Undav

    FWD · VfB Stuttgart

    provisional
    Mins
    71
    Proj.
    0.97
    O 1.5
    26%
    Model /90
    1.22
    041%
    133%
    217%
    36%
    42%
    51%
    6+0%
  • Leon Goretzka

    MID · FC Bayern München

    provisional
    Mins
    57
    Proj.
    0.94
    O 1.5
    25%
    Model /90
    1.47
    044%
    131%
    215%
    36%
    42%
    51%
    6+0%
  • Michael Olise

    FWD · FC Bayern München

    provisional
    Mins
    71
    Proj.
    0.94
    O 1.5
    24%
    Model /90
    1.19
    042%
    133%
    216%
    36%
    42%
    50%
    6+0%
  • Harry Kane

    FWD · FC Bayern München

    provisional
    Mins
    77
    Proj.
    0.91
    O 1.5
    23%
    Model /90
    1.07
    042%
    134%
    216%
    36%
    42%
    5+0%
  • Ermedin Demirović

    FWD · VfB Stuttgart

    provisional
    Mins
    57
    Proj.
    0.89
    O 1.5
    23%
    Model /90
    1.41
    047%
    129%
    214%
    36%
    42%
    51%
    6+0%
  • Atakan Karazor

    MID · VfB Stuttgart

    provisional
    Mins
    75
    Proj.
    0.87
    O 1.5
    22%
    Model /90
    1.04
    045%
    132%
    215%
    35%
    41%
    5+0%
  • Jamie Leweling

    FWD · VfB Stuttgart

    provisional
    Mins
    69
    Proj.
    0.84
    O 1.5
    21%
    Model /90
    1.10
    046%
    133%
    214%
    35%
    41%
    5+0%
  • Aleksandar Pavlović

    MID · FC Bayern München

    provisional
    Mins
    65
    Proj.
    0.83
    O 1.5
    21%
    Model /90
    1.15
    047%
    132%
    214%
    35%
    41%
    5+0%
  • Bilal El Khannous

    MID · VfB Stuttgart

    provisional
    Mins
    65
    Proj.
    0.83
    O 1.5
    21%
    Model /90
    1.14
    048%
    131%
    214%
    35%
    41%
    5+0%
  • Angelo Stiller

    MID · VfB Stuttgart

    provisional
    Mins
    83
    Proj.
    0.81
    O 1.5
    20%
    Model /90
    0.88
    046%
    134%
    214%
    34%
    41%
    5+0%
  • Julian Chabot

    DEF · VfB Stuttgart

    provisional
    Mins
    79
    Proj.
    0.81
    O 1.5
    20%
    Model /90
    0.93
    047%
    133%
    214%
    34%
    41%
    5+0%
  • Joshua Kimmich

    MID · FC Bayern München

    provisional
    Mins
    83
    Proj.
    0.80
    O 1.5
    20%
    Model /90
    0.87
    047%
    134%
    214%
    34%
    41%
    5+0%
  • Tom Bischof

    MID · FC Bayern München

    provisional
    Mins
    50
    Proj.
    0.79
    O 1.5
    21%
    Model /90
    1.42
    054%
    125%
    212%
    35%
    42%
    51%
    6+0%
  • Jamal Musiala

    MID · FC Bayern München

    provisional
    Mins
    62
    Proj.
    0.77
    O 1.5
    19%
    Model /90
    1.12
    050%
    131%
    213%
    34%
    41%
    5+0%
  • Konrad Laimer

    DEF · FC Bayern München

    provisional
    Mins
    64
    Proj.
    0.77
    O 1.5
    19%
    Model /90
    1.08
    050%
    131%
    213%
    34%
    41%
    5+0%
  • Dayotchanculle Upamecano

    DEF · FC Bayern München

    provisional
    Mins
    81
    Proj.
    0.76
    O 1.5
    18%
    Model /90
    0.85
    048%
    134%
    213%
    34%
    41%
    5+0%
  • Finn Jeltsch

    DEF · VfB Stuttgart

    provisional
    Mins
    65
    Proj.
    0.76
    O 1.5
    19%
    Model /90
    1.04
    052%
    129%
    213%
    35%
    41%
    5+0%
  • Serge Gnabry

    FWD · FC Bayern München

    provisional
    Mins
    51
    Proj.
    0.74
    O 1.5
    18%
    Model /90
    1.30
    052%
    130%
    212%
    34%
    41%
    5+0%
  • Jonathan Tah

    DEF · FC Bayern München

    provisional
    Mins
    72
    Proj.
    0.73
    O 1.5
    18%
    Model /90
    0.92
    051%
    131%
    213%
    34%
    41%
    5+0%

20 of 43 players shown, ranked by projection.

Tackles43 playersHighest: Josha Mamadou Karaboue Vagnomann, 1.94 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.

  • provisional
    Mins
    65
    Proj.
    1.94
    O 1.5
    53%
    Model /90
    2.71
    024%
    123%
    220%
    315%
    410%
    55%
    6+3%
  • Maximilian Mittelstädt

    DEF · VfB Stuttgart

    provisional
    Mins
    74
    Proj.
    1.83
    O 1.5
    53%
    Model /90
    2.22
    020%
    127%
    224%
    316%
    48%
    53%
    6+2%
  • Angelo Stiller

    MID · VfB Stuttgart

    provisional
    Mins
    83
    Proj.
    1.73
    O 1.5
    51%
    Model /90
    1.87
    020%
    130%
    225%
    315%
    47%
    53%
    6+1%
  • José María Andrés Baixauli

    MID · VfB Stuttgart

    provisional
    Mins
    52
    Proj.
    1.66
    O 1.5
    44%
    Model /90
    2.86
    036%
    120%
    215%
    312%
    48%
    55%
    6+3%
  • Atakan Karazor

    MID · VfB Stuttgart

    provisional
    Mins
    75
    Proj.
    1.65
    O 1.5
    48%
    Model /90
    1.97
    024%
    128%
    224%
    314%
    47%
    53%
    6+1%
  • Bilal El Khannous

    MID · VfB Stuttgart

    provisional
    Mins
    65
    Proj.
    1.60
    O 1.5
    46%
    Model /90
    2.21
    027%
    127%
    222%
    314%
    47%
    53%
    6+1%
  • Julian Chabot

    DEF · VfB Stuttgart

    provisional
    Mins
    79
    Proj.
    1.49
    O 1.5
    44%
    Model /90
    1.70
    025%
    131%
    224%
    313%
    45%
    52%
    6+1%
  • Dayotchanculle Upamecano

    DEF · FC Bayern München

    provisional
    Mins
    81
    Proj.
    1.48
    O 1.5
    43%
    Model /90
    1.65
    024%
    133%
    224%
    312%
    45%
    52%
    6+1%
  • Leonidas Stergiou

    DEF · VfB Stuttgart

    provisional
    Mins
    66
    Proj.
    1.44
    O 1.5
    43%
    Model /90
    1.97
    031%
    127%
    222%
    313%
    45%
    52%
    6+1%
  • Joshua Kimmich

    MID · FC Bayern München

    provisional
    Mins
    83
    Proj.
    1.42
    O 1.5
    41%
    Model /90
    1.55
    026%
    133%
    223%
    312%
    44%
    51%
    6+0%
  • Konrad Laimer

    DEF · FC Bayern München

    provisional
    Mins
    64
    Proj.
    1.36
    O 1.5
    39%
    Model /90
    1.92
    031%
    131%
    221%
    311%
    45%
    52%
    6+1%
  • Finn Jeltsch

    DEF · VfB Stuttgart

    provisional
    Mins
    65
    Proj.
    1.33
    O 1.5
    39%
    Model /90
    1.84
    034%
    127%
    220%
    311%
    45%
    52%
    6+1%
  • Jamal Musiala

    MID · FC Bayern München

    provisional
    Mins
    62
    Proj.
    1.33
    O 1.5
    38%
    Model /90
    1.93
    031%
    131%
    221%
    311%
    44%
    52%
    6+1%
  • Aleksandar Pavlović

    MID · FC Bayern München

    provisional
    Mins
    65
    Proj.
    1.32
    O 1.5
    38%
    Model /90
    1.83
    030%
    132%
    221%
    311%
    44%
    51%
    6+0%
  • Jonathan Tah

    DEF · FC Bayern München

    provisional
    Mins
    72
    Proj.
    1.30
    O 1.5
    37%
    Model /90
    1.62
    032%
    131%
    221%
    311%
    44%
    51%
    6+0%
  • Alphonso Davies

    DEF · FC Bayern München

    provisional
    Mins
    65
    Proj.
    1.28
    O 1.5
    36%
    Model /90
    1.77
    033%
    130%
    220%
    310%
    44%
    51%
    6+1%
  • Luca Antony Jaquez

    DEF · VfB Stuttgart

    provisional
    Mins
    61
    Proj.
    1.26
    O 1.5
    35%
    Model /90
    1.87
    034%
    131%
    219%
    310%
    44%
    51%
    6+1%
  • Min-Jae Kim

    DEF · FC Bayern München

    provisional
    Mins
    75
    Proj.
    1.20
    O 1.5
    34%
    Model /90
    1.45
    034%
    132%
    221%
    39%
    43%
    51%
    6+0%
  • Josip Stanisic

    DEF · FC Bayern München

    provisional
    Mins
    68
    Proj.
    1.19
    O 1.5
    33%
    Model /90
    1.57
    035%
    132%
    219%
    39%
    43%
    51%
    6+0%
  • Ramon Hendriks

    DEF · VfB Stuttgart

    provisional
    Mins
    57
    Proj.
    1.15
    O 1.5
    32%
    Model /90
    1.82
    040%
    128%
    217%
    39%
    44%
    51%
    6+1%

20 of 43 players shown, ranked by projection.

Shots43 playersHighest: Harry Kane, 2.62 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.

  • Harry Kane

    FWD · FC Bayern München

    provisional
    Mins
    77
    Proj.
    2.62
    O 1.5
    67%
    Model /90
    3.07
    013%
    121%
    221%
    317%
    412%
    58%
    6+9%
  • Luis Fernando Díaz Marulanda

    FWD · FC Bayern München

    provisional
    Mins
    78
    Proj.
    2.43
    O 1.5
    63%
    Model /90
    2.82
    014%
    122%
    222%
    317%
    411%
    57%
    6+7%
  • Michael Olise

    FWD · FC Bayern München

    provisional
    Mins
    71
    Proj.
    2.32
    O 1.5
    60%
    Model /90
    2.96
    016%
    123%
    221%
    316%
    410%
    56%
    6+7%
  • Serge Gnabry

    FWD · FC Bayern München

    provisional
    Mins
    51
    Proj.
    1.81
    O 1.5
    47%
    Model /90
    3.18
    026%
    126%
    219%
    312%
    48%
    54%
    6+4%
  • Deniz Undav

    FWD · VfB Stuttgart

    provisional
    Mins
    71
    Proj.
    1.66
    O 1.5
    46%
    Model /90
    2.10
    026%
    128%
    221%
    313%
    47%
    53%
    6+2%
  • Jamie Leweling

    FWD · VfB Stuttgart

    provisional
    Mins
    69
    Proj.
    1.33
    O 1.5
    37%
    Model /90
    1.74
    032%
    131%
    220%
    310%
    44%
    52%
    6+1%
  • Jamal Musiala

    MID · FC Bayern München

    provisional
    Mins
    62
    Proj.
    1.29
    O 1.5
    35%
    Model /90
    1.87
    035%
    130%
    218%
    310%
    44%
    52%
    6+1%
  • Ermedin Demirović

    FWD · VfB Stuttgart

    provisional
    Mins
    57
    Proj.
    1.28
    O 1.5
    35%
    Model /90
    2.03
    038%
    128%
    217%
    39%
    45%
    52%
    6+1%
  • Joshua Kimmich

    MID · FC Bayern München

    provisional
    Mins
    83
    Proj.
    1.22
    O 1.5
    34%
    Model /90
    1.33
    033%
    133%
    220%
    39%
    44%
    51%
    6+1%
  • Chris Führich

    FWD · VfB Stuttgart

    provisional
    Mins
    56
    Proj.
    1.16
    O 1.5
    31%
    Model /90
    1.86
    039%
    130%
    217%
    38%
    44%
    51%
    6+1%
  • provisional
    Mins
    40
    Proj.
    1.05
    O 1.5
    27%
    Model /90
    2.40
    044%
    129%
    214%
    37%
    43%
    51%
    6+1%
  • Lennart Karl

    MID · FC Bayern München

    provisional
    Mins
    49
    Proj.
    1.00
    O 1.5
    26%
    Model /90
    1.83
    043%
    130%
    215%
    37%
    43%
    51%
    6+0%
  • Leon Goretzka

    MID · FC Bayern München

    provisional
    Mins
    57
    Proj.
    0.97
    O 1.5
    26%
    Model /90
    1.53
    044%
    130%
    215%
    37%
    43%
    51%
    6+0%
  • Aleksandar Pavlović

    MID · FC Bayern München

    provisional
    Mins
    65
    Proj.
    0.96
    O 1.5
    25%
    Model /90
    1.33
    043%
    132%
    216%
    36%
    42%
    51%
    6+0%
  • Badredine Bouanani

    FWD · VfB Stuttgart

    provisional
    Mins
    33
    Proj.
    0.95
    O 1.5
    24%
    Model /90
    2.62
    053%
    123%
    211%
    36%
    43%
    52%
    6+1%
  • Tiago Barreiros de Melo Tomás

    FWD · VfB Stuttgart

    provisional
    Mins
    38
    Proj.
    0.93
    O 1.5
    23%
    Model /90
    2.23
    049%
    128%
    213%
    36%
    43%
    51%
    6+1%
  • Tom Bischof

    MID · FC Bayern München

    provisional
    Mins
    50
    Proj.
    0.90
    O 1.5
    24%
    Model /90
    1.63
    052%
    124%
    213%
    37%
    43%
    51%
    6+1%
  • Bilal El Khannous

    MID · VfB Stuttgart

    provisional
    Mins
    65
    Proj.
    0.77
    O 1.5
    19%
    Model /90
    1.06
    051%
    130%
    213%
    35%
    41%
    50%
    6+0%
  • Angelo Stiller

    MID · VfB Stuttgart

    provisional
    Mins
    83
    Proj.
    0.76
    O 1.5
    18%
    Model /90
    0.82
    049%
    133%
    213%
    34%
    41%
    5+0%
  • Atakan Karazor

    MID · VfB Stuttgart

    provisional
    Mins
    75
    Proj.
    0.69
    O 1.5
    16%
    Model /90
    0.82
    053%
    130%
    212%
    33%
    41%
    5+0%

20 of 43 players shown, ranked by projection.

Shots on target40 playersHighest: Harry Kane, 1.32 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.

  • Harry Kane

    FWD · FC Bayern München

    provisional
    Mins
    77
    Proj.
    1.32
    O 0.5
    69%
    Model /90
    1.54
    031%
    132%
    220%
    310%
    44%
    52%
    6+1%
  • Michael Olise

    FWD · FC Bayern München

    provisional
    Mins
    71
    Proj.
    1.04
    O 0.5
    60%
    Model /90
    1.33
    040%
    132%
    217%
    37%
    43%
    51%
    6+0%
  • Luis Fernando Díaz Marulanda

    FWD · FC Bayern München

    provisional
    Mins
    78
    Proj.
    1.00
    O 0.5
    60%
    Model /90
    1.17
    040%
    133%
    217%
    37%
    42%
    51%
    6+0%
  • Serge Gnabry

    FWD · FC Bayern München

    provisional
    Mins
    51
    Proj.
    0.66
    O 0.5
    44%
    Model /90
    1.16
    056%
    129%
    211%
    33%
    41%
    5+0%
  • Deniz Undav

    FWD · VfB Stuttgart

    provisional
    Mins
    71
    Proj.
    0.65
    O 0.5
    45%
    Model /90
    0.83
    055%
    130%
    211%
    33%
    41%
    5+0%
  • Ermedin Demirović

    FWD · VfB Stuttgart

    provisional
    Mins
    57
    Proj.
    0.60
    O 0.5
    41%
    Model /90
    0.95
    059%
    127%
    210%
    33%
    41%
    5+0%
  • Jamie Leweling

    FWD · VfB Stuttgart

    provisional
    Mins
    69
    Proj.
    0.56
    O 0.5
    41%
    Model /90
    0.74
    059%
    129%
    29%
    32%
    40%
    5+0%
  • Jamal Musiala

    MID · FC Bayern München

    provisional
    Mins
    62
    Proj.
    0.52
    O 0.5
    38%
    Model /90
    0.75
    062%
    127%
    28%
    32%
    4+1%
  • Chris Führich

    FWD · VfB Stuttgart

    provisional
    Mins
    56
    Proj.
    0.49
    O 0.5
    36%
    Model /90
    0.78
    064%
    126%
    28%
    32%
    4+0%
  • Lennart Karl

    MID · FC Bayern München

    provisional
    Mins
    49
    Proj.
    0.42
    O 0.5
    32%
    Model /90
    0.77
    068%
    124%
    26%
    31%
    4+0%
  • Joshua Kimmich

    MID · FC Bayern München

    provisional
    Mins
    83
    Proj.
    0.41
    O 0.5
    32%
    Model /90
    0.44
    068%
    126%
    26%
    31%
    4+0%
  • Aleksandar Pavlović

    MID · FC Bayern München

    provisional
    Mins
    65
    Proj.
    0.36
    O 0.5
    29%
    Model /90
    0.51
    071%
    123%
    25%
    31%
    4+0%
  • provisional
    Mins
    40
    Proj.
    0.35
    O 0.5
    27%
    Model /90
    0.79
    073%
    121%
    25%
    31%
    4+0%
  • Badredine Bouanani

    FWD · VfB Stuttgart

    provisional
    Mins
    33
    Proj.
    0.34
    O 0.5
    25%
    Model /90
    0.93
    075%
    118%
    25%
    31%
    4+0%
  • Leon Goretzka

    MID · FC Bayern München

    provisional
    Mins
    57
    Proj.
    0.32
    O 0.5
    26%
    Model /90
    0.51
    074%
    121%
    24%
    31%
    4+0%
  • Tiago Barreiros de Melo Tomás

    FWD · VfB Stuttgart

    provisional
    Mins
    38
    Proj.
    0.32
    O 0.5
    25%
    Model /90
    0.77
    075%
    120%
    24%
    31%
    4+0%
  • Tom Bischof

    MID · FC Bayern München

    provisional
    Mins
    50
    Proj.
    0.29
    O 0.5
    23%
    Model /90
    0.53
    077%
    118%
    24%
    31%
    4+0%
  • Bilal El Khannous

    MID · VfB Stuttgart

    provisional
    Mins
    65
    Proj.
    0.27
    O 0.5
    23%
    Model /90
    0.37
    077%
    119%
    23%
    3+0%
  • Atakan Karazor

    MID · VfB Stuttgart

    provisional
    Mins
    75
    Proj.
    0.25
    O 0.5
    21%
    Model /90
    0.30
    079%
    118%
    23%
    3+0%
  • Angelo Stiller

    MID · VfB Stuttgart

    provisional
    Mins
    83
    Proj.
    0.25
    O 0.5
    22%
    Model /90
    0.27
    078%
    119%
    23%
    3+0%

20 of 40 players shown, ranked by projection.

Fouls won43 playersHighest: Michael Olise, 1.28 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.

  • Michael Olise

    FWD · FC Bayern München

    provisional
    Mins
    71
    Proj.
    1.28
    O 1.5
    35%
    Model /90
    1.63
    033%
    131%
    219%
    310%
    44%
    52%
    6+1%
  • Luis Fernando Díaz Marulanda

    FWD · FC Bayern München

    provisional
    Mins
    78
    Proj.
    1.14
    O 1.5
    31%
    Model /90
    1.32
    036%
    133%
    218%
    38%
    43%
    51%
    6+0%
  • Tom Bischof

    MID · FC Bayern München

    provisional
    Mins
    50
    Proj.
    1.01
    O 1.5
    27%
    Model /90
    1.82
    049%
    124%
    213%
    37%
    44%
    52%
    6+1%
  • Jamal Musiala

    MID · FC Bayern München

    provisional
    Mins
    62
    Proj.
    0.99
    O 1.5
    26%
    Model /90
    1.43
    043%
    131%
    216%
    37%
    42%
    51%
    6+0%
  • Harry Kane

    FWD · FC Bayern München

    provisional
    Mins
    77
    Proj.
    0.98
    O 1.5
    26%
    Model /90
    1.15
    041%
    133%
    216%
    36%
    42%
    51%
    6+0%
  • Jamie Leweling

    FWD · VfB Stuttgart

    provisional
    Mins
    69
    Proj.
    0.95
    O 1.5
    25%
    Model /90
    1.25
    043%
    132%
    216%
    36%
    42%
    51%
    6+0%
  • Angelo Stiller

    MID · VfB Stuttgart

    provisional
    Mins
    83
    Proj.
    0.95
    O 1.5
    25%
    Model /90
    1.02
    042%
    133%
    216%
    36%
    42%
    51%
    6+0%
  • Atakan Karazor

    MID · VfB Stuttgart

    provisional
    Mins
    75
    Proj.
    0.89
    O 1.5
    23%
    Model /90
    1.06
    046%
    131%
    215%
    36%
    42%
    50%
    6+0%
  • Joshua Kimmich

    MID · FC Bayern München

    provisional
    Mins
    83
    Proj.
    0.84
    O 1.5
    21%
    Model /90
    0.92
    046%
    133%
    214%
    35%
    41%
    50%
    6+0%
  • Deniz Undav

    FWD · VfB Stuttgart

    provisional
    Mins
    71
    Proj.
    0.84
    O 1.5
    21%
    Model /90
    1.06
    047%
    132%
    214%
    35%
    42%
    50%
    6+0%
  • Ermedin Demirović

    FWD · VfB Stuttgart

    provisional
    Mins
    57
    Proj.
    0.80
    O 1.5
    20%
    Model /90
    1.27
    051%
    128%
    213%
    35%
    42%
    51%
    6+0%
  • Min-Jae Kim

    DEF · FC Bayern München

    provisional
    Mins
    75
    Proj.
    0.79
    O 1.5
    20%
    Model /90
    0.95
    049%
    131%
    213%
    35%
    41%
    5+0%
  • Aleksandar Pavlović

    MID · FC Bayern München

    provisional
    Mins
    65
    Proj.
    0.67
    O 1.5
    16%
    Model /90
    0.93
    054%
    130%
    211%
    33%
    41%
    5+0%
  • Bilal El Khannous

    MID · VfB Stuttgart

    provisional
    Mins
    65
    Proj.
    0.65
    O 1.5
    15%
    Model /90
    0.89
    056%
    129%
    211%
    33%
    41%
    5+0%
  • Julian Chabot

    DEF · VfB Stuttgart

    provisional
    Mins
    79
    Proj.
    0.65
    O 1.5
    15%
    Model /90
    0.74
    055%
    131%
    211%
    33%
    41%
    5+0%
  • Serge Gnabry

    FWD · FC Bayern München

    provisional
    Mins
    51
    Proj.
    0.63
    O 1.5
    14%
    Model /90
    1.10
    057%
    128%
    210%
    33%
    41%
    5+0%
  • Leon Goretzka

    MID · FC Bayern München

    provisional
    Mins
    57
    Proj.
    0.63
    O 1.5
    14%
    Model /90
    0.98
    057%
    128%
    210%
    33%
    41%
    5+0%
  • Tiago Barreiros de Melo Tomás

    FWD · VfB Stuttgart

    provisional
    Mins
    38
    Proj.
    0.61
    O 1.5
    14%
    Model /90
    1.45
    060%
    126%
    29%
    33%
    41%
    50%
    6+0%
  • Maximilian Mittelstädt

    DEF · VfB Stuttgart

    provisional
    Mins
    74
    Proj.
    0.59
    O 1.5
    13%
    Model /90
    0.72
    058%
    129%
    210%
    33%
    41%
    5+0%
  • Lennart Karl

    MID · FC Bayern München

    provisional
    Mins
    49
    Proj.
    0.58
    O 1.5
    13%
    Model /90
    1.06
    060%
    128%
    29%
    33%
    41%
    5+0%

20 of 43 players shown, ranked by projection.

Cards43 playersHighest: Atakan Karazor, 0.15 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.

  • Atakan Karazor

    MID · VfB Stuttgart

    provisional
    Mins
    75
    Proj.
    0.15
    O 0.5
    14%
    Model /90
    0.18
    086%
    113%
    2+1%
  • Konrad Laimer

    DEF · FC Bayern München

    provisional
    Mins
    64
    Proj.
    0.15
    O 0.5
    14%
    Model /90
    0.21
    086%
    113%
    2+1%
  • Leon Goretzka

    MID · FC Bayern München

    provisional
    Mins
    57
    Proj.
    0.15
    O 0.5
    14%
    Model /90
    0.23
    086%
    112%
    2+1%
  • Dayotchanculle Upamecano

    DEF · FC Bayern München

    provisional
    Mins
    81
    Proj.
    0.14
    O 0.5
    13%
    Model /90
    0.16
    087%
    112%
    2+1%
  • Finn Jeltsch

    DEF · VfB Stuttgart

    provisional
    Mins
    65
    Proj.
    0.14
    O 0.5
    13%
    Model /90
    0.19
    087%
    112%
    2+1%
  • Joshua Kimmich

    MID · FC Bayern München

    provisional
    Mins
    83
    Proj.
    0.14
    O 0.5
    13%
    Model /90
    0.15
    087%
    112%
    2+1%
  • Jonathan Tah

    DEF · FC Bayern München

    provisional
    Mins
    72
    Proj.
    0.14
    O 0.5
    13%
    Model /90
    0.17
    087%
    112%
    2+1%
  • Bilal El Khannous

    MID · VfB Stuttgart

    provisional
    Mins
    65
    Proj.
    0.14
    O 0.5
    13%
    Model /90
    0.19
    087%
    112%
    2+1%
  • Julian Chabot

    DEF · VfB Stuttgart

    provisional
    Mins
    79
    Proj.
    0.14
    O 0.5
    13%
    Model /90
    0.16
    087%
    112%
    2+1%
  • Luis Fernando Díaz Marulanda

    FWD · FC Bayern München

    provisional
    Mins
    78
    Proj.
    0.13
    O 0.5
    12%
    Model /90
    0.15
    088%
    111%
    2+1%
  • Michael Olise

    FWD · FC Bayern München

    provisional
    Mins
    71
    Proj.
    0.13
    O 0.5
    12%
    Model /90
    0.16
    088%
    111%
    2+1%
  • Angelo Stiller

    MID · VfB Stuttgart

    provisional
    Mins
    83
    Proj.
    0.13
    O 0.5
    12%
    Model /90
    0.14
    088%
    111%
    2+1%
  • Deniz Undav

    FWD · VfB Stuttgart

    provisional
    Mins
    71
    Proj.
    0.12
    O 0.5
    11%
    Model /90
    0.15
    089%
    110%
    2+1%
  • Maximilian Mittelstädt

    DEF · VfB Stuttgart

    provisional
    Mins
    74
    Proj.
    0.12
    O 0.5
    11%
    Model /90
    0.14
    089%
    110%
    2+1%
  • Tom Bischof

    MID · FC Bayern München

    provisional
    Mins
    50
    Proj.
    0.12
    O 0.5
    11%
    Model /90
    0.21
    089%
    110%
    2+1%
  • Aleksandar Pavlović

    MID · FC Bayern München

    provisional
    Mins
    65
    Proj.
    0.11
    O 0.5
    11%
    Model /90
    0.16
    089%
    110%
    2+1%
  • Leonidas Stergiou

    DEF · VfB Stuttgart

    provisional
    Mins
    66
    Proj.
    0.11
    O 0.5
    11%
    Model /90
    0.15
    089%
    110%
    2+1%
  • Min-Jae Kim

    DEF · FC Bayern München

    provisional
    Mins
    75
    Proj.
    0.11
    O 0.5
    10%
    Model /90
    0.13
    090%
    110%
    2+1%
  • José María Andrés Baixauli

    MID · VfB Stuttgart

    provisional
    Mins
    52
    Proj.
    0.11
    O 0.5
    10%
    Model /90
    0.19
    090%
    19%
    2+1%
  • Jamal Musiala

    MID · FC Bayern München

    provisional
    Mins
    62
    Proj.
    0.11
    O 0.5
    10%
    Model /90
    0.16
    090%
    19%
    2+1%

20 of 43 players shown, ranked by projection.

Saves43 playersHighest: Alexander Nübel, 3.48 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.

  • Alexander Nübel

    GK · VfB Stuttgart

    provisional
    Mins
    90
    Proj.
    3.48
    O 2.5
    64%
    Model /90
    3.48
    05%
    113%
    219%
    320%
    417%
    512%
    6+16%
  • Jonas Urbig

    GK · FC Bayern München

    provisional
    Mins
    83
    Proj.
    2.61
    O 2.5
    47%
    Model /90
    2.83
    011%
    120%
    222%
    319%
    413%
    58%
    6+8%
  • Manuel Neuer

    GK · FC Bayern München

    provisional
    Mins
    87
    Proj.
    2.16
    O 2.5
    36%
    Model /90
    2.22
    014%
    125%
    225%
    318%
    410%
    55%
    6+3%
  • Angelo Stiller

    MID · VfB Stuttgart

    provisional
    Mins
    83
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Julian Chabot

    DEF · VfB Stuttgart

    provisional
    Mins
    79
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Atakan Karazor

    MID · VfB Stuttgart

    provisional
    Mins
    75
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Maximilian Mittelstädt

    DEF · VfB Stuttgart

    provisional
    Mins
    74
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Deniz Undav

    FWD · VfB Stuttgart

    provisional
    Mins
    71
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Jamie Leweling

    FWD · VfB Stuttgart

    provisional
    Mins
    69
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Bilal El Khannous

    MID · VfB Stuttgart

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

    DEF · VfB Stuttgart

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

    DEF · VfB Stuttgart

    provisional
    Mins
    66
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Luca Antony Jaquez

    DEF · VfB Stuttgart

    provisional
    Mins
    61
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Ramon Hendriks

    DEF · VfB Stuttgart

    provisional
    Mins
    57
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Ermedin Demirović

    FWD · VfB Stuttgart

    provisional
    Mins
    57
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Chris Führich

    FWD · VfB Stuttgart

    provisional
    Mins
    56
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Dayotchanculle Upamecano

    DEF · FC Bayern München

    provisional
    Mins
    81
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Joshua Kimmich

    MID · FC Bayern München

    provisional
    Mins
    83
    Proj.
    0.00
    O 2.5
    Model /90
    0.00
    0100%
    1+0%
  • Luis Fernando Díaz Marulanda

    FWD · FC Bayern München

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

20 of 43 players shown, ranked by projection.