1. Bundesliga Frauen

1. Bundesliga Frauen - Hauptrunde

1. Bundesliga Frauen Best players OPPOSITE
PlayerPlayedServeServeBlockBlockAttackAttackRanking
  MS#=/TotSv ind.Sv ind.#=/TotBl ind.Bl ind.#=/TotSp ind.Sp ind.Index

1

Drpa Marta
(SC Potsdam)

5

20

12

11

4

76

0.0186

0.0186

12

10

0

30

0.014

0.014

87

17

7

204

6.1765

6.1765

0.53984

2

Drewniok Kimberly
(SSC Palmberg Schwerin)

6

22

14

10

7

93

0.0204

0.0204

3

3

6

26

0.0029

0.0029

69

16

16

181

4.4972

4.4972

0.53392

3

Finley Canace
(Schwarz-Weiß Erfurt)

6

21

9

11

8

66

0.0189

0.0189

7

3

12

28

0.0078

0.0078

60

24

10

175

3.12

3.12

0.51915

4

Patockova Tereza
(VfB Suhl LOTTO Thüringen)

5

18

11

12

3

67

0.0171

0.0171

5

6

0

16

0.0061

0.0061

39

14

13

107

2.0187

2.0187

0.49413

5

Vanjak Ivana
(USC Münster)

5

19

5

7

5

72

0.0122

0.0122

8

8

3

29

0.0097

0.0097

68

15

8

173

4.9422

4.9422

0.46703

6

Scholten Iris
(Rote Raben Vilsbiburg)

5

14

4

2

5

36

0.0134

0.0134

3

6

0

21

0.0045

0.0045

30

7

10

93

1.957

1.957

0.45751

7

van Daelen Deborah
(Allianz MTV Stuttgart)

4

14

2

1

3

35

0.0085

0.0085

2

1

7

15

0.0034

0.0034

36

6

1

85

4.7765

4.7765

0.42394

8

Dancheva Maria
(Rote Raben Vilsbiburg)

3

10

1

2

3

16

0.0092

0.0092

3

0

0

8

0.0069

0.0069

13

6

2

42

1.1905

1.1905

0.41732

9

Agost Taylor
(Ladies in black Aachen)

5

20

3

3

1

50

0.0048

0.0048

3

2

6

23

0.0036

0.0036

70

11

13

166

5.5422

5.5422

0.39416

10

Neuhaus Frauke
(NawaRo Straubing)

5

18

5

12

0

45

0.0056

0.0056

3

3

1

11

0.0034

0.0034

63

18

13

158

3.6456

3.6456

0.39272

11

Doshkova Ralina
(SSC Palmberg Schwerin)

3

7

3

2

0

14

0.006

0.006

1

1

3

5

0.002

0.002

6

7

4

26

-1.3462

-1.3462

0.37054

12

Kastrup Liza
(USC Münster)

3

10

0

2

1

25

0.0023

0.0023

2

2

3

9

0.0046

0.0046

17

2

5

43

2.3256

2.3256

0.35846

13

Hamson Jennifer
(VC Wiesbaden)

4

9

2

2

0

15

0.0027

0.0027

4

0

0

6

0.0054

0.0054

9

1

4

28

1.2857

1.2857

0.35788

14

Berger Lara
(VCO Berlin)

6

13

3

5

0

21

0.0037

0.0037

2

2

0

7

0.0025

0.0025

17

12

9

55

-0.9455

-0.9455

0.35313

15

Große Scharmann Lena
(NawaRo Straubing)

5

14

2

3

0

26

0.0023

0.0023

6

2

3

11

0.0068

0.0068

19

14

2

73

0.5753

0.5753

0.35231

16

Weske Emilia
(SC Potsdam)

5

10

1

3

1

10

0.0023

0.0023

0

0

0

1

0

0

1

0

0

4

2.5

2.5

0.3426

17

Rivers Krystal
(Allianz MTV Stuttgart)

4

8

0

2

0

14

0

0

3

4

2

17

0.0051

0.0051

21

8

3

50

1.6

1.6

0.33583

18

Maase Rica
(Dresdner SC)

2

4

0

0

1

3

0.0032

0.0032

1

0

1

3

0.0032

0.0032

5

2

0

10

1.2

1.2

0.32659

19

Storck Maja
(Ladies in black Aachen)

5

13

1

0

0

6

0.0012

0.0012

2

2

0

6

0.0024

0.0024

8

5

6

29

-1.3448

-1.3448

0.32567

Ranking Calculation

Opposite

the ranking takes into account:

  • Serve Index (Sv ind.): positive serves divided the total points of both teams (ranking is available only if the player has made at least one serve per set)

  • Attack Index (Sp ind.): positive attacks minus negative attacks divided the total attacks (ranking is available only if the player has made at least three attacks per set)

  • Block Index (Bl ind.): positive blocks divided the total points of both teams

The final ranking is based on the final “index” which determines the impact of the role on the game, in other words the importance of the role towards the win probability. This final Index is calculated considering the indexes for each single skill (“ind.” columns) and a coefficient which indicates the “importance” of the role to determine the probability of success for the team. Each single skill index is calculated considering the positive and negative skills based on the number of points played from the teams and multiplied for a coefficient which indicates the importance of the skill for that role to determine the probability of success for the team. The icons next to each skill column give an idea about the “weight” of the skill determining the probability of success for the team in this role. The final Index is calculated also considering the following criteria:

  • Minimum number of Serves per set:  1

  • Minimum number of Spikes per set:  3

Serve

  • # serve ace

  • / half point

  • = serve error

Attack

  • # point

  • / blocked

  • = error

Block

  • # point

  • / Net touch

  • = hand out

Filters applied

  • Minimum number of Matches played:  1