Baltic Women`s Volleyball League 23/24

Baltic Women`s Volleyball League 23/24

Baltic Women`s Volleyball League 23/24 Best players OPPOSITE
PlayerPlayedServeServeBlockBlockAttackAttackRanking
  MS#=/TotSv ind.Sv ind.#=/TotBl ind.Bl ind.#=/TotSp ind.Sp ind.Index

1

Ivanova Anastasija
(SUFA klubs/DU)

1

4

6

4

1

17

0.0398

0.0398

3

3

0

7

0.017

0.017

9

6

1

32

0.25

0.25

0.7012

2

Krustkalne Katrina Paula
(Riga Volleyball School/LU)

16

58

26

31

12

199

0.0139

0.0139

28

13

0

51

0.0102

0.0102

144

31

18

359

15.3482

15.3482

0.53634

3

Suvi Ingris
(TÜ/Bigbank)

22

76

26

31

14

206

0.011

0.011

16

24

0

59

0.0044

0.0044

162

46

28

499

13.4028

13.4028

0.49207

4

Sola Līva
(VK Jelgava)

15

54

18

19

12

162

0.0126

0.0126

21

27

1

72

0.0088

0.0088

149

47

33

445

8.373

8.373

0.48739

5

Janceviča Anastasija
(SUFA klubs/DU)

1

3

1

2

1

10

0.0154

0.0154

0

0

0

0

0

0

13

3

2

35

0.6857

0.6857

0.46385

6

Laurecka Dagmara Helena
(SUFA klubs/DU)

10

33

13

12

5

102

0.0118

0.0118

15

33

0

92

0.0099

0.0099

74

37

15

299

2.4281

2.4281

0.45177

7

Kvedaraitė Danielė
(Jonavos ,,Aušrinė'' )

11

38

12

9

2

135

0.0077

0.0077

21

12

0

45

0.0115

0.0115

116

22

9

331

9.7583

9.7583

0.45144

8

Lember Dzintra
(TalTech)

21

67

15

29

9

164

0.0073

0.0073

18

17

1

53

0.0055

0.0055

118

54

31

356

6.2107

6.2107

0.42257

9

Regute Amanda
(VK Jelgava)

4

13

3

8

3

41

0.0089

0.0089

3

0

1

12

0.0045

0.0045

24

9

7

84

1.2381

1.2381

0.41202

10

Kuusk Ave
(TÜ/Bigbank)

16

49

10

6

2

98

0.0046

0.0046

9

11

1

35

0.0034

0.0034

94

32

15

260

8.8577

8.8577

0.40841

11

Šaparauskaitė Agnė
(Jonavos ,,Aušrinė'' )

5

10

8

3

0

27

0.0097

0.0097

0

0

0

0

0

0

7

3

2

27

0.7407

0.7407

0.40812

12

Palk Freia Liisa
(Audentes SG/NK)

16

50

11

20

4

125

0.0055

0.0055

12

15

0

41

0.0044

0.0044

80

33

16

231

6.71

6.71

0.40792

13

Struka Katrīna
(RSU/MSG)

12

45

5

32

1

95

0.0027

0.0027

21

19

0

61

0.0095

0.0095

128

41

17

316

9.9684

9.9684

0.4041

14

Paukštytė Martyna
(Kaunas-VDU)

18

55

9

19

7

142

0.0051

0.0051

6

18

0

30

0.0019

0.0019

126

62

18

378

6.6931

6.6931

0.40085

15

Čelnova Anete
(Riga Volleyball School/LU)

10

33

5

9

3

75

0.0046

0.0046

3

10

0

13

0.0017

0.0017

75

16

14

200

7.425

7.425

0.3997

16

Savukynaitė Ida Marija
(Kaunas-VDU)

15

52

7

14

5

123

0.0045

0.0045

21

11

0

46

0.0079

0.0079

92

42

21

333

4.5285

4.5285

0.39247

17

Runce Bonija
(RSU/MSG)

13

40

5

11

1

77

0.0026

0.0026

3

8

1

21

0.0013

0.0013

37

18

8

125

3.52

3.52

0.36228

18

Mindrika Elina
(SUFA klubs/DU)

2

4

1

0

0

5

0.0039

0.0039

0

0

0

0

0

0

1

0

0

2

2

2

0.35586

19

Mandel Karmen
(Audentes SG/NK)

16

27

5

11

2

32

0.0026

0.0026

4

5

0

14

0.0015

0.0015

11

9

7

41

-3.2927

-3.2927

0.34676

20

Talvar Anu
(TalTech)

14

33

4

7

1

55

0.0022

0.0022

3

6

0

16

0.0013

0.0013

4

1

1

14

4.7143

4.7143

0.34334

21

Liniņa Linda
(VK Jelgava)

1

3

0

2

0

8

0

0

0

2

0

6

0

0

9

5

1

29

0.3103

0.3103

0.32443

22

Ancāne Paula
(SUFA klubs/DU)

1

2

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0.32305

23

Zariņa Katrīna Laura
(Riga Volleyball School/LU)

1

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0.32305

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