Latvijas čempionāts sievietēm 2018/2019

LČ siev. - Pamatturnīrs

Latvijas čempionāts sievietēm 2018/2019 Best players MIDDLE BLOCKER
PlayerPlayedServeServeBlockBlockAttackAttackRanking
  MS#=/TotSv ind.Sv ind.#=/TotBl ind.Bl ind.#=/TotSp ind.Sp ind.Index

1

Tarasenko Darja
(VK miLATss)

16

60

21

13

0

194

0,0084

0,0084

46

27

0

168

0,0185

0,0185

91

12

11

243

16,7901

16,7901

0,55536

2

Ozola Lāsma
(Rīgas Volejbola skola)

19

75

46

50

4

270

0,0157

0,0157

38

19

0

77

0,0119

0,0119

40

26

7

189

2,7778

2,7778

0,55024

3

Rozīte Simona
(VK Jelgava)

15

59

27

15

4

212

0,012

0,012

26

20

0

113

0,0101

0,0101

83

17

7

178

19,5562

19,5562

0,53763

4

Pētersone Alise
(MSĢ/ZELTALEJA)

12

51

24

19

1

160

0,0117

0,0117

22

12

0

57

0,0103

0,0103

118

22

14

309

13,534

13,534

0,52499

5

Urbāne Monta
(Mārupes SC)

11

45

19

17

0

136

0,0102

0,0102

23

18

0

102

0,0124

0,0124

91

41

18

311

4,6302

4,6302

0,50798

6

Šverna Antra
(VK Gulbene)

6

20

10

7

2

52

0,0144

0,0144

5

0

0

10

0,006

0,006

29

15

6

78

2,0513

2,0513

0,49739

7

Sola Līva
(VK Jelgava)

16

62

15

15

4

187

0,0069

0,0069

30

11

0

83

0,011

0,011

165

44

10

371

18,5499

18,5499

0,4958

8

Strazdiņa Monta
(RSU/MVS)

8

28

11

11

1

82

0,0093

0,0093

11

11

0

39

0,0086

0,0086

26

10

5

80

3,85

3,85

0,4731

9

Melle Diāna
(VK Gulbene)

5

16

2

3

3

34

0,0074

0,0074

7

2

0

9

0,0104

0,0104

18

8

5

54

1,4815

1,4815

0,46385

10

Stelpe Arta
(SK Babīte)

2

8

3

4

1

26

0,0111

0,0111

2

2

0

4

0,0056

0,0056

7

5

0

23

0,6957

0,6957

0,46344

11

Jurdža Annija
(MSĢ/ZELTALEJA)

10

39

17

11

2

117

0,0105

0,0105

3

7

0

28

0,0017

0,0017

91

30

23

281

5,274

5,274

0,44073

12

Alehina Iveta
(VK miLATss)

17

64

13

22

1

151

0,0052

0,0052

16

54

0

166

0,0059

0,0059

146

44

9

426

13,9718

13,9718

0,4382

13

Miķelsone Gundega
(VK Gulbene)

3

7

2

3

1

15

0,0074

0,0074

3

0

0

10

0,0074

0,0074

2

1

4

8

-2,625

-2,625

0,43635

14

Toča Diāna
(MSĢ/ZELTALEJA)

5

13

9

5

0

40

0,0098

0,0098

1

2

0

13

0,0011

0,0011

11

1

1

41

2,8537

2,8537

0,42645

15

Gordejeva Jekaterina
(Rīgas Volejbola skola)

13

31

15

16

0

87

0,0072

0,0072

9

0

0

27

0,0043

0,0043

10

4

1

50

3,1

3,1

0,42486

16

Brīvule Menarda
(MSĢ/ZELTALEJA)

9

35

10

1

0

90

0,0063

0,0063

4

2

0

13

0,0025

0,0025

50

10

5

138

8,8768

8,8768

0,41617

17

Melne Agnese
(RSU/MVS)

4

14

4

1

1

38

0,0087

0,0087

1

7

0

12

0,0017

0,0017

2

3

0

28

-0,5

-0,5

0,41477

18

Dzierkale Kristīne
(LLU)

3

12

3

1

0

36

0,0059

0,0059

1

0

0

24

0,002

0,002

35

7

3

80

3,75

3,75

0,39958

19

Balcere Aiva
(Mārupes SC)

8

31

5

2

0

72

0,0037

0,0037

4

9

0

50

0,0029

0,0029

18

11

1

78

2,3846

2,3846

0,38469

20

Vilcāne Agnese
(VK Gulbene)

1

4

1

1

0

6

0,0061

0,0061

0

0

0

0

0

0

4

2

1

18

0,2222

0,2222

0,38285

21

Lece Alise
(SK Babīte)

1

4

1

1

0

16

0,0054

0,0054

0

2

0

2

0

0

13

4

3

32

0,75

0,75

0,37823

22

Krīgale Karlīne
(VK miLATss)

5

8

1

1

1

16

0,0024

0,0024

0

0

0

0

0

0

1

0

0

5

1,6

1,6

0,35154

23

Baltiņa Mairita
(VK Jelgava)

1

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0,33246

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