LČ Nacionālā līga sievietēm 2025/2026

LČ Nacionālā Līga sievietēm 2025/2026

LČ Nacionālā līga sievietēm 2025/2026 Best players MIDDLE BLOCKER
PlayerPlayedServeServeBlockBlockAttackAttackRanking
  MS#=/TotSv ind.Sv ind.#=/TotBl ind.Bl ind.#=/TotSp ind.Sp ind.Index

1

Vabiščeviča Diana
(Daugavpils Sporta skola)

4

12

12

3

9

62

0,0353

0,0353

13

4

0

17

0,0218

0,0218

23

2

2

27

8,4444

8,4444

0,7696

2

Franckeviča Jana
(Daugavpils Sporta skola)

9

30

10

7

16

104

0,0201

0,0201

18

14

0

42

0,0139

0,0139

41

22

1

84

6,4286

6,4286

0,60831

3

Kursīte Evelīna
(Daugavpils Sporta skola)

13

37

17

5

13

141

0,0157

0,0157

20

7

0

40

0,0104

0,0104

31

8

4

58

12,1207

12,1207

0,55772

4

Oša Estere
(Murjāņu Sporta ģimnāzija)

19

70

43

22

12

302

0,0181

0,0181

6

9

0

23

0,002

0,002

174

67

22

530

11,2264

11,2264

0,52256

5

Brūvere Keita Kintija
(Jūrmalas volejbola klubs / Jūrmalas sporta skola)

15

47

25

20

8

148

0,0144

0,0144

22

22

3

65

0,0096

0,0096

22

16

8

81

-1,1605

-1,1605

0,51554

6

Cālīte Lita
(Liepājas sporta spēļu skola)

14

55

13

13

1

139

0,0061

0,0061

28

16

1

74

0,0123

0,0123

88

17

6

181

19,7514

19,7514

0,49959

7

Preikše Karmena Emīlija
(Murjāņu Sporta ģimnāzija)

19

70

18

43

7

238

0,0082

0,0082

34

32

3

107

0,0112

0,0112

53

23

13

153

7,7778

7,7778

0,48844

8

Rozenbaha Ketlīna Melisa
(RSU 2)

17

60

17

28

5

174

0,0081

0,0081

25

19

2

78

0,0092

0,0092

43

11

5

116

13,9655

13,9655

0,48533

9

Šveiduka Elizabete
(Liepājas sporta spēļu skola)

15

58

8

15

3

130

0,0045

0,0045

30

9

2

55

0,0122

0,0122

44

10

2

97

19,134

19,134

0,48291

10

Juršāne-Piņķe Alise
(Jūrmalas volejbola klubs / Jūrmalas sporta skola)

14

51

5

19

2

100

0,0031

0,0031

34

21

1

77

0,0152

0,0152

60

18

7

158

11,2975

11,2975

0,47538

11

Kjakste Elza
(Mārupes SC)

8

26

2

8

7

85

0,0078

0,0078

9

8

1

36

0,0078

0,0078

39

5

1

79

10,8608

10,8608

0,46713

12

Rozīte Simona
(Mārupes SC)

5

13

5

3

3

49

0,0108

0,0108

1

7

0

14

0,0013

0,0013

15

2

4

30

3,9

3,9

0,43878

13

Bikava Rēzija
(RSU 2)

3

10

0

2

0

21

0

0

8

5

0

15

0,016

0,016

4

4

0

19

0

0

0,43172

14

Vītola Tīna
(Liepājas sporta spēļu skola)

14

44

16

17

4

104

0,0086

0,0086

9

2

1

16

0,0039

0,0039

9

4

1

24

7,3333

7,3333

0,42862

15

Belouško Karlīna
(Jūrmalas volejbola klubs / Jūrmalas sporta skola)

11

23

11

21

3

58

0,0083

0,0083

5

5

1

16

0,003

0,003

11

9

2

32

0

0

0,42034

16

Brīvule Līva
(Mārupes SC)

5

13

5

9

0

32

0,0069

0,0069

3

7

0

20

0,0041

0,0041

11

4

1

32

2,4375

2,4375

0,41968

17

Ērgle-Bīmane Vita
(Jūrmalas volejbola klubs / Jūrmalas sporta skola)

9

20

4

5

1

34

0,0037

0,0037

2

6

0

8

0,0015

0,0015

14

13

5

60

-1,3333

-1,3333

0,36944

18

Ivanova Katrīna Telma
(RSU 2)

3

7

1

4

1

23

0,0041

0,0041

0

2

0

5

0

0

1

1

0

7

0

0

0,36586

19

Cēpure Agate
(Murjāņu Sporta ģimnāzija)

14

20

2

2

1

16

0,0013

0,0013

1

4

0

5

0,0004

0,0004

6

8

5

37

-3,7838

-3,7838

0,3286

Ranking Calculation

Middle-Blocker

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:  1

Serve

  • # serve ace

  • / half point

  • #NOME?

Attack

  • # point

  • / blocked

  • #NOME?

Block

  • # point

  • / Net touch

  • #NOME?

Filters applied

  • Minimum number of Matches played:  1