MEVZA League (M) 2020/2021

Main phase (M)

MEVZA League (M) 2020/2021 Best players MIDDLE BLOCKER
PlayerPlayedBlockBlockServeServeAttackAttackRanking
  MS#=/TotBl ind.Bl ind.#=/TotSv ind.Sv ind.#=/TotSp ind.Sp ind.Index

1

BORRIS Maciej
(Union Raiffeisen WALDVIERTEL (AUT))

11

43

42

45

0

108

0.0218

0.0218

4

29

4

122

0.0042

0.0042

52

6

9

100

15.91

15.91

0.48838

2

ŠTALEKAR Sašo
(OK Calcit KAMNIK (SLO))

12

46

34

47

1

124

0.0162

0.0162

8

23

6

143

0.0067

0.0067

61

9

5

103

20.9903

20.9903

0.47624

3

TOUKHTEH Amir Hossein
(ACH Volley LJUBLJANA (SLO))

10

32

16

30

5

62

0.0102

0.0102

15

35

9

115

0.0153

0.0153

43

7

6

71

13.5211

13.5211

0.47075

4

MIRANDA DE ALCANTARA Victor Hugo
(SK Zadruga AICH/DOB (AUT))

12

39

28

41

0

95

0.0152

0.0152

6

27

4

118

0.0054

0.0054

73

10

9

124

16.9839

16.9839

0.45742

5

PURIĆ Diko
(OK Calcit KAMNIK (SLO))

10

40

20

33

0

81

0.0109

0.0109

3

15

6

146

0.0049

0.0049

43

0

5

65

23.3846

23.3846

0.43983

6

VAIOPOULOS Evangelos
(Union Raiffeisen WALDVIERTEL (AUT))

12

42

28

41

0

89

0.0133

0.0133

2

14

1

111

0.0014

0.0014

37

10

0

80

14.175

14.175

0.42151

7

JERONČIČ Rok
(OK Calcit KAMNIK (SLO))

5

14

8

9

0

24

0.0097

0.0097

6

14

1

51

0.0085

0.0085

8

2

1

15

4.6667

4.6667

0.4196

8

VIDEČNIK Matic
(ACH Volley LJUBLJANA (SLO))

11

38

14

31

1

59

0.0081

0.0081

5

15

2

119

0.0041

0.0041

47

4

10

83

15.1084

15.1084

0.40612

9

UNTERBERGER Clemens
(UVC Holding GRAZ (AUT))

10

31

18

26

0

60

0.0106

0.0106

2

15

0

100

0.0012

0.0012

41

5

4

76

13.0526

13.0526

0.40329

10

UREMOVIČ Filip
(OK MERKUR MARIBOR (SLO))

11

37

11

26

1

71

0.0056

0.0056

3

18

3

143

0.003

0.003

35

1

0

52

24.1923

24.1923

0.40137

11

CAFUTA Miha
(OK MERKUR MARIBOR (SLO))

11

37

19

30

0

90

0.0098

0.0098

4

19

1

119

0.0026

0.0026

25

7

3

54

10.2778

10.2778

0.40071

12

PAVLOVIĆ Uroš
(ACH Volley LJUBLJANA (SLO))

5

14

9

18

0

29

0.011

0.011

2

0

0

31

0.0024

0.0024

17

2

1

30

6.5333

6.5333

0.40062

13

GRABMÜLLER Nicolai
(SK Zadruga AICH/DOB (AUT))

1

3

1

4

1

6

0.0073

0.0073

0

0

1

4

0.0073

0.0073

2

0

0

3

2

2

0.39546

14

KÜHL Lukas
(SK Zadruga AICH/DOB (AUT))

8

22

12

16

1

47

0.0099

0.0099

0

5

0

55

0

0

29

4

3

45

10.7556

10.7556

0.38996

15

HRUŠKA Michal
(SK Zadruga AICH/DOB (AUT))

9

29

5

30

0

54

0.0036

0.0036

5

11

1

112

0.0043

0.0043

30

2

4

52

13.3846

13.3846

0.37882

16

REITER David
(UVC Holding GRAZ (AUT))

11

33

8

25

1

46

0.0044

0.0044

2

14

1

92

0.0016

0.0016

45

4

6

79

14.6203

14.6203

0.37258

17

BLAGINOV Valentin Dimitrov
(Union Raiffeisen WALDVIERTEL (AUT))

12

24

8

11

0

26

0.0038

0.0038

4

9

2

69

0.0028

0.0028

18

4

2

35

8.2286

8.2286

0.36478

18

IMŠIROVIĆ Kemal
(UVC Holding GRAZ (AUT))

10

32

9

27

1

47

0.0052

0.0052

2

26

1

101

0.0017

0.0017

36

9

14

84

4.9524

4.9524

0.36219

19

RUTAR Filip
(ACH Volley LJUBLJANA (SLO))

8

23

1

3

0

6

0.0007

0.0007

4

8

4

47

0.0059

0.0059

9

0

3

14

9.8571

9.8571

0.34945

20

KOVAČIČ Tit
(OK MERKUR MARIBOR (SLO))

7

14

0

0

0

0

0

0

0

4

1

21

0.0008

0.0008

0

0

0

0

0

0

0.32251

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