Bayern Munich vs ACF Fiorentina: Who Wins? Advanced Stats, Prediction & H2H
Who is currently the better team – Bayern Munich or ACF Fiorentina? Discover advanced team stats, xG metrics, Expected Threat, full H2H records, pressing & possession profiles, visualised predictions and data-driven performance analytics.
Germany 
Bundesliga 
Italy 
Serie A 
Analyse Analyse Bayern Munich vs. ACF Fiorentina - Who Is Better?
Bayern Munich has a 1vs1 Score of 100 while ACF Fiorentina has a 1vs1 Score of 62.42, showing which team is performing better this season. View Bayern Munich's Position in 1vs1 Best Team Ranking | View ACF Fiorentina's Position in 1vs1 Best Team Ranking
ACF Fiorentina has won 587 ground duels versus 520 for Bayern Munich, with ACF Fiorentina ranking 20 and Bayern Munich ranking 16 in the league for ground duels won. See Full Ground duels won Ranking
Bayern Munich has accumulated 19.16 expected goals against while ACF Fiorentina faces 37.61, with Bayern Munich ranking 1 and ACF Fiorentina ranking 17 in the league for xG conceded. See Full Xg total conceeded Ranking
Key Stats
| Metric | Value |
|---|---|
| Goals  | 74 25 |
| Goals | 3.7 1.09 |
| Shot at goal number ⓘ Number of shots. | 366 297 |
| Shots on Goal | 272 189 |
| Goals conceeded | 18 36 |
| Goals conceeded | 0.9 1.57 |
| Matches won | 16 3 |
| Matches lost | 1 12 |
Scores
To enhance your comprehension of our performance index, we will elucidate some of its values. However, it's important to note that we cannot disclose all of them. Here are a few example: succesful passes, ball losses, goals, assists, expected goals, critical ball losses, initiating dangerous attacks, clearances, ball regains in different parts of the pitch, The 1vs1 Performance defensive Index is a sophisticated algorithm designed to assess the performance of individual players, comprising a set of 10 values. To enhance your comprehension of our performance index, we will elucidate some of its values. However, it's important to note that we cannot disclose all of them. Here are few examples: critical ball losses, clearances, ball regains in different parts of the pitch, etc The 1vs1 Performance offensive Index is a sophisticated algorithm designed to assess the performance of individual players, comprising a set of 11 values. Attacking Threat measures a player`s or teams ability to directly impact the game by creating scoring opportunities. It considers actions like dribbling past opponents, winning the ball in dangerous areas, and taking shots on goal. To enhance your comprehension of our performance index, we will elucidate some of its values. However, it's important to note that we cannot disclose all of them. Here are a few example: succesful passes, ball losses, goals, assists, expected goals, critical ball losses, initiating dangerous attacks, clearances, ball regains in different parts of the pitch, The 1vs1 Performance defensive Index is a sophisticated algorithm designed to assess the performance of individual players, comprising a set of 10 values. To enhance your comprehension of our performance index, we will elucidate some of its values. However, it's important to note that we cannot disclose all of them. Here are few examples: critical ball losses, clearances, ball regains in different parts of the pitch, etc The 1vs1 Performance offensive Index is a sophisticated algorithm designed to assess the performance of individual players, comprising a set of 11 values. Attacking Threat measures a player`s or teams ability to directly impact the game by creating scoring opportunities. It considers actions like dribbling past opponents, winning the ball in dangerous areas, and taking shots on goal. Team Form
Shooting Data & xG Analysis
All Bayern Munich`s shots on this match:
Strengths & Weaknesses
| Team | Strengths & Weaknesses | Team |
|---|---|---|
| BAY | FIO | |
| 0 | | 0 |
| 0 | | 0 |
| 0 | | 0 |
| 0 | | 0 |
| 0 | | 0 |
| 0 | | 0 |
Up To Date Stats
Bayern Munich creates 8 clear goal-scoring opportunities compared to ACF Fiorentina's 2 - highlighting their ability to fashion high-quality chances
ACF Fiorentina records 108 shots that miss the target completely versus Bayern Munich's 94 - showcasing their shooting accuracy variance
Bayern Munich completes 2953 passes from the right flank while ACF Fiorentina manages 1446 - exposing their right-sided distribution patterns
Compare Yourself
Bayern Munich Compare Bayern Munich
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Bayern Munich’s and ACF Fiorentina’s Total Squad Salary
Salary Stats
#1
Jonah Kusi-Asare
0
No.
Player
Value
#1
Jonah Kusi-Asare
0
#2
Lennart Karl
0
#3
Sacha Boey
0
#4
Manuel Neuer
0
#5
Tom Bischof
0
#6
Wisdom Mike
0
#7
Jonas Urbig
0
#8
Alphonso Davies
0
#9
David Santos
0
#10
Cassiano Kiala
0
#11
Felipe Chavez
0
#12
Jamal Musiala
0
#13
Joshua Kimmich
0
#14
Leon Goretzka
0
#15
Min-jae Kim
0
#16
Dayot Upamecano
0
#17
Jonathan Tah
0
#18
Konrad Laimer
0
#19
Hiroki Ito
0
#20
Josip Stanisic
0
#21
Serge Gnabry
0
#22
Raphael Guerreiro
0
#23
Nicolas Jackson
1
#24
Luis Diaz
1
#25
Michael Olise
1
#26
Harry Kane
1
#27
Aleksandar Pavlovic
1
#1
Jonah Kusi-Asare
0
#2
Lennart Karl
0
#3
Tom Bischof
0
#4
Wisdom Mike
0
No.
Player
Value
#1
Jonah Kusi-Asare
0
#2
Lennart Karl
0
#3
Tom Bischof
0
#4
Wisdom Mike
0
#5
Jonas Urbig
0
#6
David Santos
0
#7
Cassiano Kiala
0
#8
Felipe Chavez
0
#9
Jamal Musiala
0
#10
Alphonso Davies
0
#11
Raphael Guerreiro
1
#12
Serge Gnabry
1
#13
Joshua Kimmich
1
#14
Harry Kane
1
#15
Manuel Neuer
1
#16
Sacha Boey
1
#17
Min-jae Kim
1
#18
Luis Diaz
1
#19
Leon Goretzka
1
#20
Dayot Upamecano
1
#21
Jonathan Tah
1
#22
Michael Olise
1
#23
Konrad Laimer
1
#24
Josip Stanisic
2
#25
Nicolas Jackson
2
#26
Hiroki Ito
2
#27
Aleksandar Pavlovic
10
#1
Jonah Kusi-Asare
0
#2
Lennart Karl
0
#3
Tom Bischof
0
#4
Wisdom Mike
0
No.
Player
Value
#1
Jonah Kusi-Asare
0
#2
Lennart Karl
0
#3
Tom Bischof
0
#4
Wisdom Mike
0
#5
Jonas Urbig
0
#6
David Santos
0
#7
Cassiano Kiala
0
#8
Felipe Chavez
0
#9
Jamal Musiala
0
#10
Manuel Neuer
1
#11
Alphonso Davies
2
#12
Min-jae Kim
3
#13
Nicolas Jackson
3
#14
Raphael Guerreiro
3
#15
Harry Kane
4
#16
Serge Gnabry
4
#17
Jonathan Tah
5
#18
Sacha Boey
8
#19
Dayot Upamecano
8
#20
Leon Goretzka
8
#21
Joshua Kimmich
10
#22
Josip Stanisic
12
#23
Hiroki Ito
13
#24
Konrad Laimer
14
#25
Luis Diaz
14
#26
Michael Olise
26
#27
Aleksandar Pavlovic
73
#1
Aleksandar Pavlovic
0.69
No.
Player
Value
#1
Aleksandar Pavlovic
1
#2
Harry Kane
1
#3
Luis Diaz
1
#4
Nicolas Jackson
0
#5
Michael Olise
0
#6
Serge Gnabry
0
#7
Raphael Guerreiro
0
#8
Konrad Laimer
0
#9
Hiroki Ito
0
#10
Leon Goretzka
0
#11
Josip Stanisic
0
#12
Dayot Upamecano
0
#13
Sacha Boey
0
#14
Joshua Kimmich
0
#15
Jonathan Tah
0
#16
Min-jae Kim
0
#17
Jamal Musiala
0
#18
Jonah Kusi-Asare
0
#19
Lennart Karl
0
#20
Manuel Neuer
0
#21
Tom Bischof
0
#22
Wisdom Mike
0
#23
Jonas Urbig
0
#24
Alphonso Davies
0
#25
David Santos
0
#26
Cassiano Kiala
0
#27
Felipe Chavez
0
Salary Stats
#1
Jacopo Fazzini
0
No.
Player
Value
#1
Jacopo Fazzini
0
#2
Dodo
0
#3
Pablo Mari
0
#4
David de Gea
0
#5
Nicolo Fagioli
0
#6
Simon Sohm
0
#7
Marin Pongracic
0
#8
Mattia Viti
0
#9
Fabiano Parisi
0
#10
Eddy Kouadio
0
#11
Edin Dzeko
0
#12
Tariq Lamptey
0
#13
Hans Nicolussi Caviglia
0
#14
Niccolo Fortini
0
#15
Abdelhamid Sabiri
0
#16
Amir Richardson
0
#17
Christian Kouame
0
#18
Giovanni Fabbian
0
#19
Jack Harrison
0
#20
Manor Solomon
0
#21
Luca Ranieri
0
#22
Pietro Comuzzo
1
#23
Robin Gosens
1
#24
Marco Brescianini
1
#25
Roberto Piccoli
1
#26
Moise Kean
1
#27
Cher Ndour
1
#28
Albert Gudmundsson
1
#29
Rolando Mandragora
2
#1
Mattia Viti
0
#2
Eddy Kouadio
0
#3
Edin Dzeko
0
#4
Niccolo Fortini
0
No.
Player
Value
#1
Mattia Viti
0
#2
Eddy Kouadio
0
#3
Edin Dzeko
0
#4
Niccolo Fortini
0
#5
Abdelhamid Sabiri
0
#6
Giovanni Fabbian
0
#7
Jack Harrison
0
#8
Christian Kouame
1
#9
Amir Richardson
2
#10
Manor Solomon
2
#11
Tariq Lamptey
2
#12
Marco Brescianini
3
#13
Moise Kean
5
#14
David de Gea
6
#15
Robin Gosens
6
#16
Fabiano Parisi
8
#17
Jacopo Fazzini
8
#18
Nicolo Fagioli
10
#19
Pablo Mari
10
#20
Roberto Piccoli
10
#21
Hans Nicolussi Caviglia
10
#22
Albert Gudmundsson
11
#23
Marin Pongracic
11
#24
Rolando Mandragora
12
#25
Luca Ranieri
14
#26
Pietro Comuzzo
15
#27
Simon Sohm
15
#28
Dodo
19
#29
Cher Ndour
24
#1
Mattia Viti
0
#2
Eddy Kouadio
0
#3
Edin Dzeko
0
#4
Niccolo Fortini
0
No.
Player
Value
#1
Mattia Viti
0
#2
Eddy Kouadio
0
#3
Edin Dzeko
0
#4
Niccolo Fortini
0
#5
Abdelhamid Sabiri
0
#6
Giovanni Fabbian
0
#7
Jack Harrison
0
#8
Christian Kouame
1
#9
Tariq Lamptey
1
#10
Amir Richardson
3
#11
David de Gea
3
#12
Moise Kean
3
#13
Marco Brescianini
3
#14
Roberto Piccoli
4
#15
Manor Solomon
6
#16
Pablo Mari
8
#17
Jacopo Fazzini
9
#18
Pietro Comuzzo
15
#19
Robin Gosens
18
#20
Simon Sohm
19
#21
Fabiano Parisi
20
#22
Hans Nicolussi Caviglia
23
#23
Cher Ndour
25
#24
Rolando Mandragora
26
#25
Marin Pongracic
28
#26
Luca Ranieri
30
#27
Albert Gudmundsson
34
#28
Nicolo Fagioli
45
#29
Dodo
98
#1
Moise Kean
1.92
#2
Roberto Piccoli
1.6
#3
Rolando Mandragora
1.26
#4
Albert Gudmundsson
1.18
No.
Player
Value
#1
Moise Kean
2
#2
Roberto Piccoli
2
#3
Rolando Mandragora
1
#4
Albert Gudmundsson
1
#5
Cher Ndour
1
#6
Marco Brescianini
1
#7
Robin Gosens
1
#8
Dodo
0
#9
Luca Ranieri
0
#10
Pietro Comuzzo
0
#11
Fabiano Parisi
0
#12
Hans Nicolussi Caviglia
0
#13
Nicolo Fagioli
0
#14
Jacopo Fazzini
0
#15
Marin Pongracic
0
#16
Simon Sohm
0
#17
Manor Solomon
0
#18
Pablo Mari
0
#19
Amir Richardson
0
#20
David de Gea
0
#21
Mattia Viti
0
#22
Eddy Kouadio
0
#23
Edin Dzeko
0
#24
Tariq Lamptey
0
#25
Niccolo Fortini
0
#26
Abdelhamid Sabiri
0
#27
Christian Kouame
0
#28
Giovanni Fabbian
0
#29
Jack Harrison
0
Bayern Munich: Where Do They Rank? A Breakdown of Their Benchmark, Average, and Weak Stats
Benchmark Stats
These are the stats where Bayern Munich is among the very best, setting the standard for the league.
Very Good Stats
These are the areas where Bayern Munich consistently performs at a high level, placing him near the top of the league.
ACF Fiorentina: Where Do They Rank? A Breakdown of Their Benchmark, Average, and Weak Stats
Very Good Stats
These are the areas where ACF Fiorentina consistently performs at a high level, placing him near the top of the league.
Average Stats
These stats show ACF Fiorentina`s solid, reliable contributions that are in line with the majority of players in his position.
Weak Stats
These are the areas where ACF Fiorentina`s performance falls below the league average.
Performance per season
Expected Threat & Involvement Analysis
Bayern Munich has an Expected Threat of 9331.71 - ranking 1 and measuring their ability to advance the ball into dangerous positions, while ACF Fiorentina generates 4727.77 Expected Threat - sitting at 8, showing which team better progresses play toward scoring opportunities and controls the attacking tempo. See Full Expected Threat Ranking
Bayern Munich has an Expected Threat against of 295.09 - placing them 18 defensively, indicating how much dangerous ball progression they allow opponents, while ACF Fiorentina concedes 412.02 Expected Threat against - ranking 12, revealing which defense better restricts opponent advances into threatening areas and maintains defensive solidity. See Full Expected Threat against Ranking
Bayern Munich recorded 198 Critical ball losses - ranking 17 in possession security, meaning they've given the ball away in trouble spots, while ACF Fiorentina suffered 175 such losses - sitting at 15, highlighting which team is more vulnerable in possession under pressure and prone to dangerous turnovers. See Full Critical ball losses Ranking
Key Preformance Indicators
| Metric | Value |
|---|---|
| Expected Threat ⓘ Expected Threat (xT) measures how much a team’s chance of scoring changes when the ball is moved from one location on the pitch to another. The pitch is divided into zones, each with a value reflecting the probability of scoring if the ball is in that zone. Every on-ball action (pass, carry, dribble, sometimes reception) gets a value equal to the increase (or decrease) in the team’s scoring probability when the ball moves from the start zone to the end zone. Summing these changes across a match or season gives a player’s or team’s total xT contributed by their actions. | 9331.71 4727.77 |
| Expected Threat Against ⓘ Expected Threat Against (often written xTA or xT against) applies the same idea from the defensive point of view. It measures how much the opponent’s chance of scoring changes during their possessions against your team. When the opposition progresses the ball into more dangerous zones, the xTA you concede increases; when you prevent progression or force the ball back into safer areas, you reduce xTA conceded. Aggregated over time, xTA describes how much threat a team allows through opponent ball progression, and at player level it can be used to evaluate how well defenders and midfielders limit dangerous ball movement. | 295.09 412.02 |
| Critical ball losses ⓘ Number of turnovers in possession in which 4 or more teammates are removed from the game (not goal side of the ball). These ball losses are particularly serious because there are few teammates behind the ball, therefore increasing the risk of conceding a goal. | 198 175 |
| Initiate dangerous attacks ⓘ Initiating dangerous attacks with the ball, play in advanced areas, penetrating the opposition defence. A deadly pass from a midfield to a the striker, who is then free in front of the goal, bypasses a certain amount of defenders. 78% of the teams with a better result in this metric won their games. | 2016 1135 |
| Xg Ratio ⓘ The ratio of the Xg value in relation to the goals scored. The lower the value, the better the goalscorer. | 0.75 1.45 |
Ratings and Scores
Compare Bayern Munich & ACF Fiorentina`s Performance
Performance Trends
Select a trend category to explore metrics with significant changes, stable performance, or areas of concern.
Shooting Data & xG Analysis
Advanced Stats & Analytics
Scores
| 1vs1 Index ⓘ To enhance your comprehension of our performance index, we will elucidate some of its values. However, it's important to note that we cannot disclose all of them. Here are a few example: succesful passes, ball losses, goals, assists, expected goals, critical ball losses, initiating dangerous attacks, clearances, ball regains in different parts of the pitch, | 100 62.42 |
| 1vs1 index defensive ⓘ The 1vs1 Performance offensive Index is a sophisticated algorithm designed to assess the performance of individual players, comprising a set of 11 values. | 86.13 59.48 |
| 1vs1 Index offensive ⓘ The 1vs1 Performance defensive Index is a sophisticated algorithm designed to assess the performance of individual players, comprising a set of 10 values. To enhance your comprehension of our performance index, we will elucidate some of its values. However, it's important to note that we cannot disclose all of them. Here are few examples: critical ball losses, clearances, ball regains in different parts of the pitch, etc | 100 61.72 |
| Offensive interventions | 125.3 122.04 |
Goals & Assists
| Goals | 74 25 |
| Assists ⓘ Creating goals, playing the final pass. | 64 16 |
| Goals by long distance shot ⓘ Goal after a shot from more than 22 metres | 2 2 |
| Goals by head ⓘ Goals by head | 11 3 |
| Penalty goals ⓘ Penalty goals | 6 5 |
| Goals by freekick ⓘ Goals by freekick | 0 0 |
| Goals by foot | 53 16 |
| Shots on Goal | 272 189 |
| Shots on goal / Goal Ratio ⓘ Describes the ratio of shots on goal and the number of goals. The ideal value would be 100% - every shot is a goal. | 15.43 5.93 |
Goals & Shots conceded
| Goals conceeded | 18 36 |
| Goals by head conceeded | 5 8 |
| Goals by foot conceeded | 11 24 |
| Shots on goal conceeded | 114 204 |
| Goals per 90 min conceeded | 0.9 1.57 |
Passing and Ball progression
| Progressive passes (PrgP) ⓘ Number of successful offensive actions by a player or a team (dribblings, passes, crosses) | 5040 3691 |
| Progressive passes received (PrgR) ⓘ Number of successful offensive actions in which a player is found as a receiver (dribblings, passes, crosses) and opponent players have been bypassed | 4067 2846 |
| Total successful passes by low pass ⓘ Pass that reaches the teammate. in this case a diagonal pass. | 11358 6848 |
| Total successful passes by diagonal pass ⓘ Pass that reaches the teammate. In this case a diagonal pass. | 262 119 |
| Total successful passes by clearance by foot ⓘ Pass that reaches the teammate. in this case a low pass. In this case a clearance. | 147 175 |
| Total successful passes by throw-ins ⓘ Pass that reaches the teammate. In this case after a throw in. | 349 300 |
| Total successful passes by corners ⓘ Pass that reaches the teammate. In this case after a corner. | 53 26 |
| Total successful passes from own box ⓘ Pass that reaches the team-mate. Here specifically: A pass FROM the ‘own box’ to another area of the field. | 631 685 |
| Total successful passes from 1st third ⓘ Pass that reaches the other player. Here specifically: A pass FROM the area ‘1st third of the field’ to another area of the field. | 1873 1924 |
| Total successful passes from 2nd third ⓘ Pass that reaches the other player. Here specifically: A pass FROM the ‘middle third’ area to another area of the field. | 7291 4504 |
| Total successful passes from final third ⓘ Pass that reaches the other player. Here specifically: A pass FROM the ‘last third’ area to another area of the field. | 3345 1475 |
| Total successful passes from opponents box ⓘ Pass that reaches the teammate. | 184 78 |
| Total successful passes from right wing ⓘ Pass that reaches the teammate. | 2953 1446 |
| Total successful passes from right half space ⓘ Pass that reaches the teammate. Here played FROM right half space | 2346 1426 |
| Total successful passes from centre ⓘ Pass that reaches the teammate. Here from the center. | 3385 2436 |
| Total successful passes from left half space ⓘ Pass that reaches the teammate. Here from the left half space | 2189 1585 |
| Total successful passes from left wing ⓘ Pass that reaches the teammate. Here from the left wing. | 2451 1773 |
| Initiate dangerous attacks ⓘ Initiating dangerous attacks with the ball, play in advanced areas, penetrating the opposition defence. A deadly pass from a midfield to a the striker, who is then free in front of the goal, bypasses a certain amount of defenders. 78% of the teams with a better result in this metric won their games. | 2016 1135 |
| Succesful passes in % by low pass ⓘ Pass that reaches the teammate. in this case a diagonal pass. | 93.87 91.99 |
| Succesful passes in % by diagonal pass ⓘ Pass that reaches the teammate. In this case a diagonal pass. | 78.68 65.03 |
| Succesful passes in % by throw-ins ⓘ Pass that reaches the teammate. In this case after a throw in. | 92.57 90.09 |
| Succesful passes in % by corners ⓘ Pass that reaches the teammate. In this case after a corner. | 62.35 43.33 |
| Succesful passes in % by clearance by foot ⓘ Pass that reaches the teammate. in this case a low pass. In this case a clearance. | 49.83 45.34 |
| Succesful passes in % from own box ⓘ Pass that reaches the team-mate. Here specifically: A pass FROM the ‘own box’ to another area of the field. | 74.24 67.35 |
| Succesful passes in % from 1st third ⓘ Pass that reaches the other player. Here specifically: A pass FROM the area ‘1st third of the field’ to another area of the field. | 84.98 82.05 |
| Succesful passes in % from 2nd third ⓘ Pass that reaches the other player. Here specifically: A pass FROM the ‘middle third’ area to another area of the field. | 92.23 86.3 |
| Succesful passes in % from final third ⓘ Pass that reaches the other player. Here specifically: A pass FROM the ‘last third’ area to another area of the field. | 85.2 72.77 |
| Succesful passes in % from opponents box ⓘ Pass that reaches the teammate. | 55.42 40.63 |
| Succesful passes in % from left wing ⓘ Pass that reaches the teammate. Here from the left half space | 88.26 77.83 |
| Succesful passes in % from left half space ⓘ Pass that reaches the teammate. Here from the left wing. | 89.46 82.98 |
| Succesful passes in % from centre ⓘ Pass that reaches the teammate. Here from the center. | 87.94 80.24 |
| Succesful passes in % from right half space ⓘ Pass that reaches the teammate. | 87.05 82.33 |
| Succesful passes in % from right wing ⓘ Pass that reaches the teammate. Here played FROM right half space | 85.62 78.42 |
Ball contacts & phases of play
| Offensive touches in phase Ball possession ⓘ Any touch on the ball where a teammate has previously been on the ball is called an offensive touch. In this case in the phase of ball possession of own team. | 10661 6535 |
| Offensive touches in phase Attacking Transition ⓘ Any touch on the ball where a teammate has previously been on the ball is called an offensive touch. In this case in the phase "attacking transition". | 1739 1450 |
| Offensive touches in phase Set Pieces ⓘ Any touch on the ball where a teammate has previously been on the ball is called an offensive touch. In this case in the opponents box. | 596 403 |
| Offensive touches in phase Second Balls ⓘ Any touch on the ball where a teammate has previously been on the ball is called an offensive touch. In this case in the phase "second ball" | 688 760 |
| Defensive touches in phase Out of Possession ⓘ Ball contacts in defensive play (when opposition team has been in possession). | 923 962 |
| Defensive touches in phase Defensive Transition ⓘ Ball contacts in defensive play (when opposition team has been in possession). | 674 681 |
| Defensive touches in phase Set Pieces ⓘ Any touch on the ball where an opposition player has previously been on the ball is called a defensive touch. Hier nach einer Standard Aktion. | 389 591 |
| Defensive touches in phase Second ball ⓘ Any touch on the ball where an opposition player has previously been on the ball is called a defensive touch. In this case after a "second ball". | 542 589 |
| Total touches in phase Set Pieces | 985 994 |
| Total touches in phase Second ball | 1230 1349 |
Ball losses
| Critical ball losses ⓘ Number of turnovers in possession in which 4 or more teammates are removed from the game (not goal side of the ball). These ball losses are particularly serious because there are few teammates behind the ball, therefore increasing the risk of conceding a goal. | 198 175 |
| Ball losses by low passes ⓘ Pass that goes to the opponent or out of play. Here by low pass | 742 596 |
| Ball losses by diagonal pass ⓘ Pass that goes to the opponent or out of play. Here by diagonal pass. | 71 64 |
| Ball losses by clearance by foot ⓘ Pass that goes to the opponent or out of play. Here by clearance. | 148 211 |
| Ball losses by headers ⓘ Pass that goes to the opponent or out of play. Here by headers. | 288 375 |
| Ball losses by throw-in ⓘ Pass that goes to the opponent or out of play. Here after a throw in. | 28 33 |
| Ball losses by corners ⓘ Pass that goes to the opponent or out of play. Here by corners | 32 34 |
| Ball losses in own box ⓘ Pass that goes to the opponent. Here specifically: the pass that is intercepted was played FROM the area ‘own penalty area’ | 219 332 |
| Ball losses in first third ⓘ Pass that goes to the opponent. Here specifically: the pass that is intercepted was played FROM the ‘first third of the pitch’ area | 331 421 |
| Ball losses in second third ⓘ Pass that goes to the opponent. Here specifically: the pass that is intercepted was played FROM the ‘centre third of the pitch’ area | 614 715 |
| Ball losses in final third ⓘ Pass that goes to the opponent. Here specifically: the pass that is intercepted was played FROM the space ‘last third of the pitch’ | 581 552 |
| Ball losses in opponent box ⓘ Pass that goes to the opponent. Here specifically: the pass that is intercepted was played FROM the area ‘opponent's box’ | 148 114 |
| Ball losses total | 1893 2134 |
Ball regains
| Ball regains total ⓘ Number of offensive captures of the ball. Conquering the ball after the opponent's pass. | 2506 2807 |
| Ball regains in own box ⓘ Number of offensive ball recoveries. Here specifically: From which area was the pass played, which was then intercepted -> here own box | 148 257 |
| Ball regains frist third of pitch ⓘ Number of offensive ball recoveries. Here specifically: From which area was the pass played, which was then intercepted -> here frist third of pitch | 498 654 |
| Ball regains second third of pitch ⓘ Number of offensive ball recoveries. Here specifically: IN which area was the pass intercepted that was played by the opponent -> here middle third | 971 992 |
| Ball regains in final third of pitch ⓘ Number of offensive ball recoveries. Here specifically: IN which area was the pass intercepted that was played by the opponent -> here last third | 420 432 |
| Ball regains in opponents box ⓘ Number of offensive ball recoveries. Here specifically: IN which area was the pass intercepted that was played by the opponent -> here the opponent's box | 129 94 |
Defensive
| Ground duels won ⓘ Won ground duel. | 520 587 |
| Ground duels lost ⓘ Lost ground duel. | 518 587 |
| Ariel duels won ⓘ Won aerial duel. | 178 253 |
| Ariel duels lost ⓘ Lost aerial duel. | 169 315 |
| Interception ⓘ Any touch on the ball where an opposition player has previously been on the ball is called a defensive touch. In this case an interception. | 589 657 |
| Ground duel ⓘ Any touch on the ball where an opposition player has previously been on the ball is called a defensive touch. In this case a ground duel. | 244 303 |
| Header defensive ⓘ Any touch on the ball where an opposition player has previously been on the ball is called a defensive touch. In this case a defensive header. | 521 566 |
| Block ⓘ Any touch on the ball where an opposition player has previously been on the ball is called a defensive touch. In this case a blocked ball. | 279 331 |
| Tackles | 1038 1174 |
| Clearances by foot | 321 425 |
| Ground duels total | 1038 1174 |
| Ground duels won % | 50.1 50 |
| Ground duels lost % | 49.9 50 |
| Ariel duels total | 347 568 |
| Ariel duels won % | 51.3 44.54 |
| Ariel duels lost % | 48.7 55.46 |
| Defensive stability ⓘ The ability to defend well | 380.6 446.1 |
Dribbles
| Progressive carries (PrgC) ⓘ Number of successful offensive dribblings with bypassed opponents by a player or a team | 856 661 |
| Succesful dribbles | 10680 7255 |
Elimination actions & Pitch
| Number of offensive actions from own box ⓘ The number of opponents a player or team has outplayed from their own box. | 346 376 |
| Number of offensive actions from 1st part of pitch ⓘ The number of opponents a player or team has outplayed FROM the first third. | 819 875 |
| Number of offensive actions from 2nd part of pitch ⓘ The number of opponents a player or team has outplayed FROM the middle third | 2454 1641 |
| Number of offensive actions from 3rd part of pitch ⓘ The number of opponents a player or team has outplayed from the final third | 1204 591 |
| Number of offensive actions in 1st part of pitch ⓘ Number of actions with which opponents could be bypassed (dribbling, passing, crossing, standard). Here specifically IN which space this pass or dribble was played -> 1st third of the pitch | 572 563 |
| Number of offensive actions in 2nd part of pitch ⓘ Number of actions with which opponents could be bypassed (dribbling, passing, crossing, standard). Here specifically IN which space this pass or dribble was played -> middle third of the pitch | 2260 1729 |
| Number of offensive actions in 3rd part of pitch ⓘ Number of actions with which opponents could be bypassed (dribbling, passing, crossing, standard). Here specifically IN which space this pass or dribble was played -> final third of the pitch | 1597 879 |
| Number of offensive actions into the opponent's box ⓘ Number of actions with which opponents could be bypassed (dribbling, passing, crossing, standard). Here specifically IN which space this pass or dribble was played -> into the box | 419 256 |
| Number of offensive actions from the right wing ⓘ Number of actions with which opponents could be bypassed (dribbling, passing, crossing, standard). Here specifically OUT of which space this pass or dribble was played -> right wing side of the pitch | 1142 658 |
| Number of offensive actions from half-right ⓘ Number of actions with which opponents could be bypassed (dribbling, passing, crossing, standard). Here specifically OUT of which space this pass or dribble was played -> right half space of the pitch | 854 566 |
| Number of offensive actions from the centre ⓘ Number of actions with which opponents could be bypassed (dribbling, passing, crossing, standard). Here specifically OUT of which space this pass or dribble was played -> center lane of the pitch | 1189 858 |
| Number of offensive actions from half-left ⓘ Number of actions with which opponents could be bypassed (dribbling, passing, crossing, standard). Here specifically OUT of which space this pass or dribble was played -> left half space of the pitch | 788 596 |
| Number of offensive actions from the left wing ⓘ Number of actions with which opponents could be bypassed (dribbling, passing, crossing, standard). Here specifically OUT of which space this pass or dribble was played -> left wing of the pitch | 959 843 |
| Number of offensive receptions in 1st part of pitch ⓘ Number of successful offensive actions in which a player is found as a receiver in the first third of the pitch and opponent players have been bypassed | 493 468 |
| Number of offensive receptions in 2nd part of pitch ⓘ Number of successful offensive actions in which a player is found as a receiver in the middle third of the pitch and opponent players have been bypassed | 1941 1430 |
| Number of offensive receptions in 3rd part of pitch ⓘ Number of successful offensive actions in which a player is found as a receiver in the last third of the pitch and opponent players have been bypassed | 1268 668 |
| Number of offensive receptions in opponent's box ⓘ Number of successful offensive actions in which a player is found as a receiver in the opponents box and opponent players have been bypassed | 307 208 |
xG
| Xg total ⓘ Shot-based xG tell how high the scoring probability of a goal shot is, taking into account many parameters. At player and team level, the shot-based xG indicate how many goals would have been statistically expected for the player or team on the basis of the goals scored. The comparison with the goals actually scored allows a statement to be made about the finishing efficiency. The same statement can be made about the defence by comparing the opponent's xG with the goals conceded. | 53.2 34.81 |
| Xg total ⓘ Shot-based xG tell how high the scoring probability of a goal shot is, taking into account many parameters. At player and team level, the shot-based xG indicate how many goals would have been statistically expected for the player or team on the basis of the goals scored. The comparison with the goals actually scored allows a statement to be made about the finishing efficiency. The same statement can be made about the defence by comparing the opponent's xG with the goals conceded. | 53.2 34.81 |
| Xg long distance ⓘ Shot-based xG tell how high the scoring probability of a goal shot is, taking into account many parameters. Here based on a long range shot (more than 22 Meters) | 1.41 1.79 |
| Xg with head ⓘ Shot-based xG tell how high the scoring probability of a goal shot is, taking into account many parameters. Here based on a header. | 5.68 5.65 |
| Xg with penalites ⓘ Shot-based xG tell how high the scoring probability of a goal shot is, taking into account many parameters. Here based on a penalty | 4.68 3.9 |
| Xg Ratio ⓘ The ratio of the Xg value in relation to the goals scored. The lower the value, the better the goalscorer. | 0.75 1.45 |
| Open play Xg ⓘ Open play Xg value | 47.45 29.8 |
| Set piece Xg ⓘ Set piece Xg | 5.12 4.9 |
| Xg average per shot ⓘ Xg average per shot | 0.15 0.12 |
| Xg with foot ⓘ Xg with foot | 41.77 24.16 |
| xG over/under ⓘ Goals minus Xg value. The higher the value, the better. If the value is high, the player has scored many goals from chances with a low Xg. A negative value indicates that the player is a not good a scoring goals. | 17.8 -10.81 |
| Goals minus Xg header ⓘ Header goals minus Xg value. The higher the value, the better. If the value is high, the player has scored many goals from chances with a low Xg. A negative value indicates that the player is a not good a scoring goals. | 5.32 -2.65 |
| Non-penalty xG (npxG) ⓘ Penalty goals minus Xg value. The higher the value, the better. If the value is high, the player has scored many goals from chances with a low Xg. A negative value indicates that the player is a not good a scoring goals. | 48.52 30.91 |
| Goals minus Xg free-kick ⓘ Free kick goals minus Xg value. The higher the value, the better. If the value is high, the player has scored many goals from chances with a low Xg. A negative value indicates that the player is a not good a scoring goals. | -0.45 -1 |
| Goals minus Xg long distance shot ⓘ Long distance goals (more than 22 meters) minus Xg value. The higher the value, the better. If the value is high, the player has scored many goals from chances with a low Xg. A negative value indicates that the player is a not good a scoring goals. | 0.59 0.21 |
| Goals minus Xg short distance shot ⓘ Short distance goals (less than 10 meters)minus Xg value. The higher the value, the better. If the value is high, the player has scored many goals from chances with a low Xg. A negative value indicates that the player is a not good a scoring goals. | 2.71 -2.19 |
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