Naiste Eesti meistrivõistlused

Naiste Eesti Meistrivõistlused

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

1

Hollas Heleene
(TalTech/Tradehouse)

14

47

15

8

14

155

0.0135

36

24

1

118

0.0167

53

6

8

129

14.2093

0.58303

2

Silm Keiu
(Saaremaa)

7

24

11

11

4

85

0.0143

16

7

1

42

0.0153

49

5

5

81

11.5556

0.57603

3

Põld Kätriin
(Audentese SG /Noortekoondis)

21

55

37

33

7

192

0.0144

44

10

4

72

0.0144

74

13

13

189

13.9683

0.5755

4

Loorman Mari
(TalTech/Tradehouse)

15

52

12

10

7

148

0.0082

45

34

3

126

0.0195

71

7

14

155

16.7742

0.55981

5

Pikk Renate
(TÜ/Bigbank)

18

48

16

16

11

144

0.0107

27

18

3

68

0.0107

69

9

11

139

16.9209

0.52523

6

Tammerik Sylvia
(TalTech/Tradehouse)

11

32

9

13

6

85

0.0097

21

13

2

56

0.0136

37

6

5

95

8.7579

0.51926

7

Simenson-Plakso Janely
(Tallinna Ülikool)

15

61

21

37

11

195

0.0125

23

15

2

77

0.009

45

11

13

114

11.2368

0.51789

8

Arak Mari
(TÜ/Bigbank)

15

41

9

13

9

137

0.0085

27

13

0

55

0.0127

66

9

13

141

12.7943

0.51022

9

Ostrov Silja
(Saaremaa)

15

42

14

9

4

145

0.0082

20

11

1

66

0.0091

52

6

5

108

15.9444

0.49005

10

Ripley Hailie
(Saaremaa)

5

15

5

8

0

34

0.0074

9

3

4

22

0.0132

30

10

2

71

3.8028

0.48608

11

Laas Laura
(TÜ/Bigbank)

3

10

0

1

0

22

0

10

0

0

13

0.0234

4

4

2

27

-0.7407

0.47882

12

Prangel Piret
(Saaremaa)

3

6

3

0

1

16

0.0117

1

2

0

7

0.0029

7

2

1

15

1.6

0.45239

13

Lamp Triinu
(Audentese SG /Noortekoondis)

4

10

3

5

2

29

0.0077

5

5

1

13

0.0077

10

2

2

20

3

0.45097

14

Reiter Laura
(TÜ/Bigbank)

16

40

14

16

4

153

0.0079

12

16

2

51

0.0053

62

12

13

159

9.3082

0.4494

15

Vengerfeldt Katariina
(TÜ/Bigbank)

8

13

4

8

5

38

0.0088

5

3

0

10

0.0049

12

3

1

33

3.1515

0.44238

16

Lebedeva Elina
(Tallinna Ülikool)

6

20

6

8

4

48

0.0098

3

5

0

15

0.0029

7

2

2

22

2.7273

0.43789

17

Raili Sepp
(Saaremaa)

13

31

4

6

4

71

0.0044

13

7

0

40

0.0071

40

3

5

75

13.2267

0.43718

18

Stamm Karmen
(TalTech/Tradehouse)

17

42

11

7

11

96

0.0085

1

4

4

19

0.0004

12

3

3

42

6

0.41641

19

Pill Liisbet
(Audentese SG /Noortekoondis)

11

25

9

15

0

65

0.0057

8

10

1

26

0.0051

11

4

3

44

2.2727

0.41571

20

Aru Kadri
(Saaremaa)

4

8

2

2

2

17

0.0075

0

0

0

0

0

13

5

2

30

1.6

0.39711

21

Tolli Birgit
(Tallinna Ülikool)

9

19

1

9

2

26

0.002

6

7

0

21

0.004

6

1

2

22

2.5909

0.37725

22

Tänav Sigrit
(Tallinna Ülikool)

10

21

3

6

2

43

0.0029

5

7

0

15

0.0029

8

2

4

31

1.3548

0.37593

23

Kalso Kulla
(KohilaVK/E-Service/Briketipoisid )

1

3

0

0

0

3

0

0

1

0

1

0

1

0

2

6

-0.5

0.3316

24

Abel Anni Ly
(Audentese SG /Noortekoondis)

1

3

0

1

0

3

0

0

3

0

6

0

0

1

0

4

-0.75

0.33118

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