OPTIBET Baltic Women`s Volleyball League 24/25

Baltic Women`s Volleyball League 24/25

OPTIBET Baltic Women`s Volleyball League 24/25 Best players WING SPIKER
PlayerPlayedServeServeBlockBlockAttackAttackReceptionReceptionRanking
  MS#=/TotSv ind.Sv ind.#=/TotBl ind.Bl ind.#=/TotSp ind.Sp ind.#=/TotRc ind.Rc ind.Index

1

Šidlauskaitė Miglė
(Jonavos ,,Aušrinė'' )

18

65

34

30

10

259

0.0158

0.0158

18

9

0

50

0.0065

0.0065

170

24

29

583

13.0446

13.0446

72

51

19

421

0.2803

0.2803

0.26389

2

Ankevica Agija
(RSU/MSG)

20

72

34

18

22

289

0.0167

0.0167

14

25

0

62

0.0042

0.0042

233

52

52

721

12.8821

12.8821

61

15

10

214

0.285

0.285

0.25962

3

Lember Nora
(TÜ/Bigbank)

16

58

32

31

11

211

0.0167

0.0167

19

16

1

47

0.0074

0.0074

201

56

44

550

10.6509

10.6509

76

48

31

445

0.1933

0.1933

0.25783

4

Ulumbelashvili Gvantsa
(Kaunas-VDU)

16

61

19

11

6

186

0.0089

0.0089

20

8

1

46

0.0071

0.0071

143

32

17

388

14.7784

14.7784

49

30

11

225

0.3511

0.3511

0.24598

5

Raitis Milja
(TalTech/Macta Beauty)

17

71

15

28

5

226

0.0064

0.0064

16

17

2

59

0.0051

0.0051

191

34

35

483

17.9337

17.9337

51

48

15

380

0.1211

0.1211

0.24508

6

Lass Marily
(TalTech/Macta Beauty)

15

65

17

10

6

235

0.0083

0.0083

15

19

3

69

0.0054

0.0054

234

46

38

651

14.977

14.977

71

18

10

336

0.378

0.378

0.23994

7

Putene Rūta
(Riga Volleyball School/LU)

18

62

35

21

15

250

0.0166

0.0166

5

7

0

24

0.0017

0.0017

142

48

31

420

9.3

9.3

42

34

22

338

0.1598

0.1598

0.2357

8

Treija Ruta
(VK Jelgava)

14

52

22

24

13

179

0.0149

0.0149

18

20

0

63

0.0077

0.0077

100

36

16

347

7.1931

7.1931

50

24

6

194

0.3247

0.3247

0.23522

9

Bidzāne Enija
(VK Jelgava)

18

71

24

32

10

248

0.011

0.011

21

20

2

68

0.0068

0.0068

195

73

50

559

9.1449

9.1449

56

34

11

238

0.3193

0.3193

0.22666

10

Rahuoja Ragne
(TalTech/Macta Beauty)

14

49

22

15

10

149

0.0126

0.0126

4

6

0

17

0.0016

0.0016

68

13

17

186

10.0108

10.0108

19

15

10

129

0.1473

0.1473

0.2228

11

JAKUTAVIČIENĖ Iryna
(Jonavos ,,Aušrinė'' )

18

58

11

13

8

174

0.0068

0.0068

23

18

0

70

0.0083

0.0083

146

27

31

476

10.7227

10.7227

9

4

5

68

0.2941

0.2941

0.22085

12

Kramena Kristine
(RSU/MSG)

10

33

9

8

7

96

0.0092

0.0092

7

5

0

17

0.004

0.004

84

13

18

205

8.5317

8.5317

27

5

6

97

0.299

0.299

0.20991

13

Makauskaitė Eglė
(Kaunas-VDU)

15

54

16

6

10

181

0.0098

0.0098

3

10

0

17

0.0011

0.0011

87

22

19

293

8.4778

8.4778

53

14

8

306

0.3529

0.3529

0.20583

14

Barkauskaitė Emilija
(Jonavos ,,Aušrinė'' )

18

65

14

20

12

213

0.0093

0.0093

4

19

0

34

0.0014

0.0014

161

60

29

555

8.4324

8.4324

69

43

19

348

0.2759

0.2759

0.20449

15

Huik Annabel
(TÜ/Bigbank)

16

57

10

16

5

151

0.0058

0.0058

9

12

1

34

0.0035

0.0035

95

22

15

327

10.1101

10.1101

19

23

11

196

0.0867

0.0867

0.20343

16

Nečiporuka Paula
(RSU/MSG)

1

2

2

0

0

10

0.0174

0.0174

0

0

0

1

0

0

7

1

0

10

1.2

1.2

4

0

0

6

1

1

0.20103

17

Šlitere Šarlote
(Riga Volleyball School/LU)

12

40

12

12

7

114

0.0094

0.0094

3

6

0

20

0.0015

0.0015

91

33

16

229

7.3362

7.3362

25

27

9

258

0.1589

0.1589

0.19992

18

Regute Amanda
(VK Jelgava)

11

40

13

24

9

150

0.0117

0.0117

4

9

0

19

0.0021

0.0021

81

23

27

264

4.697

4.697

58

16

4

218

0.5183

0.5183

0.19939

19

Arak Anette
(Audentes SG/NK)

13

42

12

13

10

123

0.0115

0.0115

5

5

0

20

0.0026

0.0026

86

34

25

298

3.8054

3.8054

28

21

9

224

0.2857

0.2857

0.19556

20

Kruklite Renate Kate
(Riga Volleyball School/LU)

18

53

18

25

4

146

0.0072

0.0072

11

15

2

40

0.0036

0.0036

91

30

22

326

6.3405

6.3405

25

26

6

241

0.2282

0.2282

0.19317

21

Palk Freia Liisa
(Audentes SG/NK)

14

41

15

11

1

81

0.0077

0.0077

5

3

0

13

0.0024

0.0024

42

14

13

151

4.0728

4.0728

32

19

9

151

0.2715

0.2715

0.18325

22

Rauluševičiūtė Vilūnė
(Kaunas-VDU)

16

52

5

9

4

126

0.0032

0.0032

6

6

1

17

0.0021

0.0021

79

29

17

226

7.5929

7.5929

46

22

10

229

0.2882

0.2882

0.1819

23

Maiste Laura Liisa
(TÜ/Bigbank)

16

56

11

12

11

181

0.0085

0.0085

19

27

0

85

0.0074

0.0074

57

15

9

147

12.5714

12.5714

14

8

5

90

0.2778

0.2778

0.18011

24

Põldma Liisa
(Audentes SG/NK)

16

50

7

7

8

129

0.0064

0.0064

13

11

0

41

0.0055

0.0055

95

44

34

325

2.6154

2.6154

35

19

6

183

0.2787

0.2787

0.1801

25

Lukas Keira Liina
(Audentes SG/NK)

1

2

1

2

0

6

0.0076

0.0076

1

0

0

1

0.0076

0.0076

4

1

3

17

0

0

3

2

1

15

0.2

0.2

0.17797

26

Ergle Amanda Nikola
(VK Jelgava)

10

36

7

3

3

85

0.0056

0.0056

2

7

0

24

0.0011

0.0011

55

10

16

206

5.068

5.068

45

18

9

172

0.2674

0.2674

0.17773

27

Kovala Anna
(RSU/MSG)

12

41

8

13

4

135

0.0057

0.0057

7

10

1

27

0.0033

0.0033

59

26

18

192

3.2031

3.2031

42

13

4

184

0.3804

0.3804

0.17583

28

Kandrotaite Kamile
(Jonavos ,,Aušrinė'' )

8

18

5

3

1

50

0.0048

0.0048

6

14

0

22

0.0048

0.0048

36

18

4

119

2.1176

2.1176

0

1

0

2

0

0

0.17127

29

Pikk Renate
(TÜ/Bigbank)

5

12

3

1

1

23

0.0048

0.0048

2

0

0

2

0.0024

0.0024

6

2

2

22

1.0909

1.0909

6

2

1

21

0.4286

0.4286

0.15885

30

Kazāka Karlīna
(VK Jelgava)

12

37

8

18

4

74

0.006

0.006

1

3

0

8

0.0005

0.0005

27

8

8

103

3.9515

3.9515

16

15

3

74

0.1351

0.1351

0.15856

31

Martinsone Loreta
(RSU/MSG)

7

15

1

5

2

45

0.0026

0.0026

1

4

0

11

0.0009

0.0009

29

12

5

75

2.4

2.4

8

2

3

32

0.2812

0.2812

0.15759

32

Hunt Raili
(TalTech/Macta Beauty)

9

18

2

5

1

27

0.0018

0.0018

1

1

0

8

0.0006

0.0006

18

2

8

65

2.2154

2.2154

5

2

1

33

0.1818

0.1818

0.1543

33

Liniņa Linda
(VK Jelgava)

3

11

0

4

2

33

0.0037

0.0037

0

2

0

5

0

0

7

6

5

47

-0.9362

-0.9362

14

5

1

36

0.3056

0.3056

0.14863

34

Mestere Dārta
(VK Jelgava)

12

33

3

3

0

45

0.0015

0.0015

3

1

0

4

0.0015

0.0015

18

6

4

70

3.7714

3.7714

14

9

4

59

0.1356

0.1356

0.14762

35

Nemme Madara
(VK Jelgava)

3

5

1

2

0

6

0.0017

0.0017

0

1

0

1

0

0

2

2

2

6

-1.6667

-1.6667

3

0

0

11

0.7273

0.7273

0.14551

36

Vali Kadi-Lii
(Audentes SG/NK)

11

27

1

8

1

29

0.0013

0.0013

1

5

0

7

0.0006

0.0006

14

10

4

61

0

0

10

10

10

71

-0.0282

-0.0282

0.14549

37

Juzenaite Monika
(Jonavos ,,Aušrinė'' )

13

19

2

2

0

26

0.001

0.001

0

1

0

2

0

0

4

7

1

36

-2.1111

-2.1111

1

6

1

31

0.1613

0.1613

0.1437

38

Kiaušaitė Kamilė
(Kaunas-VDU)

6

8

1

1

1

7

0.0018

0.0018

0

0

0

1

0

0

0

0

0

5

0

0

3

0

0

8

0.625

0.625

0.14105

39

Šimkuse Liene
(VK Jelgava)

1

2

0

0

0

1

0

0

0

0

0

0

0

0

0

0

1

1

-2

-2

3

0

0

4

1

1

0.14105

Ranking Calculation

Wing-spiker

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)

  • Reception Index (Rc ind.): positive receptions minus negative receptions divided the total receptions (ranking is available only if the player has made at least three receptions 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 Receptions per set:  3

  • Minimum number of Spikes per set:  3

Serve

  • # serve ace

  • / half point

  • = serve error

Reception

  • # perfect

  • / half point

  • = error

Attack

  • # point

  • / blocked

  • = error

Block

  • # point

  • / Net touch

  • = hand out

Filters applied

  • Minimum number of Matches played:  1