Naiste Eesti meistrivõistlused

Naiste Eesti Meistrivõistlused

Naiste Eesti meistrivõistlused Best players MIDDLE BLOCKER
PlayerPlayedServeBlockAttackRanking
  MS#=/TotSv ind.#=/TotBl ind.#=/TotSp ind.Index

1

Pekkenen Lisandra
(Rae Spordikool/VIASTON)

1

3

1

1

3

11

0.031

2

3

0

8

0.0155

1

0

0

2

1.5

0.69429

2

Arak Anette
(Rae Spordikool/VIASTON)

1

3

2

2

3

18

0.0273

2

0

1

3

0.0109

2

0

0

7

0.8571

0.63978

3

Peit Eliisa
(TalTech/Tradehouse)

8

34

14

7

13

128

0.0194

18

10

1

44

0.0129

76

12

7

172

11.2674

0.60398

4

Tänav Sirli
(Tallinna Ülikool/Kikas)

3

7

5

7

2

27

0.0189

5

4

1

13

0.0135

2

3

0

6

-1.1667

0.58246

5

Põld Kätriin
(Tallinna Ülikool/Kikas)

11

39

18

25

5

138

0.0135

29

13

1

67

0.0171

66

10

11

152

11.5461

0.58098

6

Hollas Eliise
(TÜ/Bigbank)

11

41

12

6

7

149

0.0102

30

28

0

94

0.0162

74

9

7

136

17.4853

0.55721

7

Teesalu Vanessa
(Viljandi Metall)

1

4

1

0

2

17

0.0164

1

1

0

5

0.0055

6

0

3

14

0.8571

0.5099

8

Pill Liisbet
(Audentese SG /Noortekoondis)

13

48

5

15

12

127

0.0079

25

36

1

95

0.0117

59

9

6

124

17.0323

0.50663

9

Kask Mirjam Karoliine
(Rae Spordikool/VIASTON)

9

30

9

14

3

88

0.0085

18

6

7

44

0.0127

14

5

0

48

5.625

0.49583

10

Kandimaa Lill
(TBD-Biodiscovery Tartu)

3

11

4

4

0

20

0.0089

5

3

0

15

0.0112

15

2

0

36

3.9722

0.4868

11

Maiste Laura Liisa
(Tallinna Ülikool/Kikas)

9

30

7

15

7

90

0.01

10

13

1

38

0.0071

18

3

4

54

6.1111

0.47353

12

Lamp Triinu
(Rae Spordikool/VIASTON)

8

25

7

7

6

75

0.0105

8

9

2

30

0.0064

18

8

5

52

2.4038

0.46654

13

Arak Mari
(TÜ/Bigbank)

12

41

9

9

3

141

0.006

18

24

0

86

0.009

35

9

6

87

9.4253

0.45762

14

Stamm Karmen
(TalTech/Tradehouse)

8

32

12

5

4

82

0.0115

4

5

1

23

0.0029

6

0

1

26

6.1538

0.44732

15

Vengerfeldt Katariina
(TÜ/Bigbank)

9

22

7

14

1

50

0.0057

10

5

1

26

0.0071

31

3

5

67

7.5522

0.4379

16

Nälk Hanna Liise
(Viljandi Metall)

2

8

1

1

2

20

0.0078

2

2

1

9

0.0052

14

2

0

28

3.4286

0.43658

17

Karm Agnes
(TBD-Biodiscovery Tartu)

1

5

0

4

0

11

0

2

2

0

11

0.0104

7

0

0

9

3.8889

0.40285

18

Reiter Laura
(TÜ/Bigbank)

11

31

7

5

3

78

0.0054

4

16

0

29

0.0022

41

6

10

127

6.1024

0.40163

19

Kuuse Maret
(Tallinna Ülikool/Kikas)

7

16

3

4

4

43

0.0066

0

2

0

4

0

30

6

1

83

4.4337

0.39498

20

Rei Kaisa
(Viljandi Metall)

1

4

0

0

1

16

0.005

0

0

0

2

0

1

0

0

5

0.8

0.37426

21

Põldma Liisa
(Audentese SG /Noortekoondis)

8

17

2

4

3

42

0.0036

2

5

0

15

0.0014

4

3

2

22

-0.7727

0.36886

22

Sova Johanna
(Tallinna Ülikool/Kikas)

9

18

0

3

0

9

0

1

9

1

15

0.0007

4

3

0

12

1.5

0.33651

23

Annus Anni
(Rae Spordikool/VIASTON)

1

2

0

1

0

4

0

0

2

0

2

0

1

0

0

5

0.4

0.33314

24

Laar Merii
(Rae Spordikool/VIASTON)

4

4

0

1

0

4

0

0

0

0

0

0

0

0

0

0

0

0.33246

25

Vähi Greteli
(TBD-Biodiscovery Tartu)

1

1

0

0

0

4

0

0

0

0

0

0

0

0

0

1

0

0.33246

26

Hiie Berit
(Tallinna Ülikool/Kikas)

1

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0.33246

27

Kauksi Kätriin
(BARRUS/Võru VK)

1

1

0

1

0

1

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

  • = serve error

Attack

  • # point

  • / blocked

  • = error

Block

  • # point

  • / Net touch

  • = hand out

Filters applied

  • Minimum number of Matches played:  1