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

Aigner-Swesey Delainey
(VC Wiesbaden)

21

82

28

42

18

305

0.0119

0.0119

35

10

13

79

0.0091

0.0091

209

53

44

586

15.6724

15.6724

0.51812

2

Drpa Marta
(SC Potsdam)

22

88

23

39

21

256

0.0111

0.0111

18

7

15

63

0.0046

0.0046

261

70

42

752

17.4362

17.4362

0.51414

3

Lippmann Louisa
(Schweriner SC)

20

72

15

33

10

201

0.0079

0.0079

31

7

35

115

0.0098

0.0098

269

62

38

655

18.5771

18.5771

0.49567

4

Iwohn Nele
(Köpenicker SC Berlin)

21

70

18

38

18

208

0.0104

0.0104

8

8

18

55

0.0023

0.0023

163

61

25

497

10.8451

10.8451

0.47091

5

Mc Mahon Elizabeth Ann
(Dresdner SC)

21

77

13

39

5

196

0.005

0.005

31

2

21

102

0.0087

0.0087

251

65

39

631

17.9382

17.9382

0.46443

6

Wilson Erica
(USC Münster)

18

66

17

27

10

214

0.0087

0.0087

8

15

7

49

0.0026

0.0026

214

58

49

576

12.2604

12.2604

0.4627

7

van Daelen Deborah
(Allianz MTV Stuttgart)

20

56

10

10

15

154

0.0078

0.0078

9

4

11

38

0.0028

0.0028

99

20

18

294

11.619

11.619

0.45109

8

Whitney Aiyana
(Allianz MTV Stuttgart)

19

50

6

14

12

113

0.0058

0.0058

16

3

15

54

0.0052

0.0052

115

28

23

289

11.0727

11.0727

0.43299

9

Mesa Luaces Liana
(Rote Raben Vilsbiburg)

16

51

8

21

7

145

0.0056

0.0056

8

16

3

55

0.003

0.003

141

40

27

341

11.0674

11.0674

0.42768

10

Baciu Iona Maria
(Ladies in Black Aachen)

19

66

3

14

5

151

0.0025

0.0025

9

9

12

57

0.0028

0.0028

154

31

33

406

14.6305

14.6305

0.41728

11

Patockova Tereza
(VfB 91 Suhl)

20

51

11

21

1

121

0.0037

0.0037

14

4

4

36

0.0043

0.0043

104

30

24

293

8.7031

8.7031

0.40103

12

Neuhaus Frauke
(Ladies in Black Aachen)

16

47

12

29

2

95

0.005

0.005

7

9

10

30

0.0025

0.0025

63

23

20

192

4.8958

4.8958

0.3917

13

Valongo de Castro Juliana "Lia"
(VfB 91 Suhl)

19

53

8

12

7

140

0.0049

0.0049

7

5

11

32

0.0023

0.0023

75

25

30

274

3.8686

3.8686

0.38545

14

Holstein Marie
(Köpenicker SC Berlin)

13

33

4

14

4

67

0.0036

0.0036

5

2

11

27

0.0022

0.0022

48

14

9

169

4.8817

4.8817

0.37875

15

Rolfzen Amber
(Dresdner SC)

10

30

1

7

3

75

0.0025

0.0025

10

2

17

56

0.0062

0.0062

45

13

11

144

4.375

4.375

0.37112

16

Große Scharmann Lena
(VC Olympia Berlin)

20

49

4

24

4

88

0.0025

0.0025

5

2

11

34

0.0016

0.0016

71

24

23

222

5.2973

5.2973

0.37058

17

Drewniok Kimberly
(SC Potsdam)

17

28

2

4

1

12

0.001

0.001

1

0

3

11

0.0003

0.0003

31

10

5

95

4.7158

4.7158

0.34464

18

Piest Madleen
(Schwarz-Weiß Erfurt)

17

33

2

5

5

61

0.0029

0.0029

0

2

5

12

0

0

30

20

14

123

-1.0732

-1.0732

0.34261

19

Mach Annalena
(VC Wiesbaden)

20

46

6

15

1

94

0.0019

0.0019

3

1

1

6

0.0008

0.0008

18

5

6

66

4.8788

4.8788

0.33984

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