Naiste Eesti meistrivõistlused

Naiste Eesti Meistrivõistlused

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

1

Pill Liisbet
(TÜ/Bigbank)

17

59

23

24

11

186

0.0128

44

42

2

121

0.0166

78

13

5

178

19.8876

0.58761

2

Kask Mirjam Karoliine
(Rae Spordikool/VIASTON)

7

25

8

10

9

77

0.0148

16

4

0

24

0.0139

41

4

5

86

9.3023

0.56713

3

Põld Kätriin
(TalTech/Tradehouse)

16

56

23

16

2

176

0.0102

33

25

6

106

0.0134

101

13

10

198

22.0606

0.54781

4

Tammel Kairin
(TBD Pharmatech Tartu)

17

57

22

35

19

209

0.0158

22

26

0

64

0.0085

137

42

19

421

10.2898

0.54303

5

Karm Agnes
(TBD Pharmatech Tartu)

13

42

6

21

9

87

0.0081

36

18

0

69

0.0194

29

9

6

113

5.2035

0.53621

6

Vengerfeldt Katariina
(TÜ/Bigbank)

3

10

8

9

1

34

0.019

1

2

0

8

0.0021

9

2

0

28

2.5

0.51411

7

Arak Mari
(TÜ/Bigbank)

17

62

11

21

14

217

0.0092

23

38

2

114

0.0084

70

7

9

138

24.2609

0.50983

8

Kandimaa Lill
(TBD Pharmatech Tartu)

11

40

19

13

9

128

0.0164

7

0

0

8

0.0041

97

34

23

311

5.1447

0.50926

9

Peit Eliisa
(TalTech/Tradehouse)

12

42

8

11

7

150

0.0076

17

25

3

88

0.0087

71

9

4

140

17.4

0.48464

10

Pohlak Marie
(Rae Spordikool/VIASTON)

14

49

11

12

9

161

0.0087

17

10

0

34

0.0074

53

10

6

145

12.5034

0.47649

11

Hiie Berit
(Viimsi/Tallinna Ülikool)

16

48

25

38

0

147

0.0105

13

9

1

39

0.0054

48

15

7

132

9.4545

0.47328

12

Maiste Laura Liisa
(TÜ/Bigbank)

15

38

11

18

10

114

0.009

10

4

2

18

0.0043

79

23

13

218

7.4954

0.44921

13

Sild Kristel
(TBD Pharmatech Tartu)

15

43

11

28

6

109

0.0076

12

18

0

46

0.0054

28

11

5

73

7.0685

0.44341

14

Reier Laureen
(Viljandi Metall)

2

7

1

3

0

20

0.0032

4

3

0

18

0.0129

8

1

2

20

1.75

0.4433

15

Põldma Liisa
(Rae Spordikool/VIASTON)

11

29

14

11

2

86

0.009

6

5

0

19

0.0034

41

14

7

110

5.2727

0.4391

16

Tänav Sirli
(Viimsi/Tallinna Ülikool)

15

49

11

25

3

117

0.0063

13

20

0

44

0.0059

50

9

15

144

8.8472

0.43852

17

Tugedam Karmen
(BARRUS/Võru VK)

1

4

0

0

0

8

0

3

1

0

6

0.0165

2

2

3

14

-0.8571

0.43323

18

Provotorov Liisa
(BARRUS/Võru VK)

2

3

1

3

0

6

0.0028

2

0

0

2

0.0057

1

0

2

8

-0.375

0.38989

19

Lamp Triinu
(Rae Spordikool/VIASTON)

4

9

1

1

1

32

0.0031

2

5

0

8

0.0031

7

2

3

19

0.9474

0.37843

20

Kauksi Kätriin
(BARRUS/Võru VK)

13

26

5

17

3

57

0.0042

0

5

0

11

0

22

18

3

110

0.2364

0.36704

21

Sova Johanna
(TalTech/Tradehouse)

2

6

0

0

0

2

0

1

2

0

10

0.0025

3

1

1

8

0.75

0.34842

22

Laar Merii
(Rae Spordikool/VIASTON)

2

2

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0.33246

23

Allik Maarja
(Viljandi Metall)

1

1

0

0

0

1

0

0

0

0

0

0

0

0

0

1

0

0.33246

24

Rand Susanna
(Viimsi/Tallinna Ülikool)

1

1

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

  • = serve error

Attack

  • # point

  • / blocked

  • = error

Block

  • # point

  • / Net touch

  • = hand out

Filters applied

  • Minimum number of Matches played:  1