SUPER LIGA 2018/2019 ( M )

2.stupanj natjecanja ( M )

SUPER LIGA 2018/2019 ( M ) Best players MIDDLE BLOCKER
PlayerPlayedBlockBlockServeServeAttackAttackRanking
  MS#=/TotBl ind.Bl ind.#=/TotSv ind.Sv ind.#=/TotSp ind.Sp ind.Index

1

Sabljak Matija
(HAOK Mladost)

4

14

11

11

0

22

0,0183

0,0183

2

6

3

60

0,0083

0,0083

19

2

0

31

7,6774

7,6774

0,47429

2

Perić Stipe
(OK Mladost Ribola Kaštela)

5

21

16

26

0

55

0,0176

0,0176

3

10

4

74

0,0077

0,0077

16

4

2

38

5,5263

5,5263

0,4634

3

Dukić Sandro
(HAOK Mladost)

6

20

10

18

0

28

0,0117

0,0117

2

9

6

70

0,0094

0,0094

15

1

2

28

8,5714

8,5714

0,44197

4

Orešković Ivan
(OK Sisak)

2

7

5

0

0

5

0,0158

0,0158

1

4

1

33

0,0063

0,0063

9

1

0

19

2,9474

2,9474

0,44175

5

Zelenika Hrvoje
(OKM Centrometal)

3

11

5

0

0

5

0,0111

0,0111

4

5

0

46

0,0088

0,0088

22

3

0

34

6,1471

6,1471

0,43157

6

Pavlović Fran
(MOK Rijeka)

4

15

9

25

0

36

0,0135

0,0135

2

4

1

43

0,0045

0,0045

16

2

1

30

6,5

6,5

0,42508

7

Šućur Kristijan
(MOK Mursa - Osijek)

3

10

4

10

0

17

0,0093

0,0093

0

5

4

34

0,0093

0,0093

6

1

2

20

1,5

1,5

0,41534

8

Palinkaš Marijan
(OKM Centrometal)

4

15

6

0

0

6

0,0097

0,0097

3

3

0

35

0,0049

0,0049

16

2

0

28

7,5

7,5

0,40667

9

Janko Daniel
(OK Rovinj)

4

14

7

1

0

8

0,0105

0,0105

0

7

1

34

0,0015

0,0015

23

9

1

46

3,9565

3,9565

0,3894

10

Lasić Luka
(MOK Rijeka)

4

15

4

8

0

14

0,006

0,006

3

4

1

45

0,006

0,006

14

2

5

29

3,6207

3,6207

0,38452

11

Mitrašinović Tomislav
(HAOK Mladost)

5

10

6

10

0

17

0,0083

0,0083

0

3

1

25

0,0014

0,0014

6

1

1

15

2,6667

2,6667

0,37415

12

Šimunić Borna
(MOK Mursa - Osijek)

3

10

2

7

0

11

0,0046

0,0046

1

2

1

23

0,0046

0,0046

7

2

0

14

3,5714

3,5714

0,37036

13

Marčić Ivo
(OK Split)

5

19

3

0

0

3

0,0037

0,0037

3

4

1

67

0,005

0,005

15

3

2

35

5,4286

5,4286

0,36987

14

Wolf Leon
(OK Sisak)

1

2

0

0

0

0

0

0

1

0

0

3

0,0079

0,0079

0

0

0

1

0

0

0,3542

15

Duraković Arnel
(OK Sisak)

1

4

1

0

0

1

0,0053

0,0053

0

3

0

14

0

0

5

0

0

13

1,5385

1,5385

0,34951

16

Rovis Antonio
(OK Rovinj)

4

14

1

0

0

1

0,0015

0,0015

2

6

1

41

0,0045

0,0045

4

2

1

15

0,9333

0,9333

0,34852

17

Đekić Simon
(OK Rovinj)

1

3

1

0

0

1

0,0047

0,0047

0

1

0

8

0

0

1

0

0

3

1

1

0,34534

18

Gudelj Ivan
(OK Split)

4

12

1

0

0

1

0,0017

0,0017

2

6

0

25

0,0034

0,0034

2

1

0

11

1,0909

1,0909

0,34276

19

Kulušić Ivan
(OK Mladost Ribola Kaštela)

4

13

0

3

0

3

0

0

1

3

1

23

0,0027

0,0027

0

0

0

0

0

0

0,33112

20

Šimić Leo
(OK Sisak)

1

3

0

0

0

0

0

0

0

1

0

6

0

0

5

3

1

21

0,1429

0,1429

0,31933

21

Šimić Domagoj
(OK Sisak)

1

3

0

0

0

0

0

0

0

1

0

5

0

0

2

2

0

5

0

0

0,31911

22

Rnjak Jakov
(OK Split)

1

1

0

0

0

0

0

0

0

1

0

1

0

0

0

0

0

0

0

0

0,31911

23

Novak Ivan
(OKM Centrometal)

1

1

0

0

0

0

0

0

0

0

0

3

0

0

0

0

0

1

0

0

0,31911

24

Bešlić Živko
(MOK Mursa - Osijek)

1

1

0

0

0

0

0

0

0

0

0

2

0

0

0

0

0

0

0

0

0,31911

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