SUPERLIGA (Ž) 2023/2024

Prvi krug natjecanja

SUPERLIGA (Ž) 2023/2024 Best players OPPOSITE
PlayerPlayedServeBlockAttackRanking
  MS#=/TotSv ind.#=/TotBl ind.#=/TotSp ind.Index

1

Barić Doris
(OK Kelteks (Ž))

22

88

42

47

17

343

0,0156

27

26

1

79

0,0071

393

81

77

975

21,2103

0,57771

2

Babić Lucia
(OK Dinamo)

21

77

40

46

13

286

0,0159

30

54

0

145

0,009

292

68

52

747

17,7296

0,56579

3

Strize Nina
(ŽOK Ribola Kaštela)

22

88

35

51

22

285

0,0148

33

26

1

84

0,0085

302

85

63

776

17,4639

0,55327

4

Mihaljević Andrea
(HAOK Mladost (Ž))

19

65

17

45

19

219

0,0127

20

28

0

72

0,0071

241

69

28

594

15,7576

0,52359

5

Glavinić Katarina
(OK Split (Ž))

22

76

18

13

10

259

0,0085

33

39

1

103

0,0101

246

48

55

627

17,3333

0,49596

6

Barišić Ana
(OK Don Bosco)

2

8

3

2

3

25

0,0175

1

0

0

1

0,0029

12

2

2

38

1,6842

0,4929

7

Ambulija Bojana
(OK Nebo)

6

23

12

7

4

90

0,0151

10

18

1

44

0,0095

74

23

12

207

4,3333

0,49178

8

Delić Lucija
(OK Brda)

20

72

19

27

11

256

0,0094

46

48

0

110

0,0145

216

43

49

676

13,2071

0,48926

9

Pavačić Tea
(HAOK Rijeka CO)

11

39

13

25

5

139

0,0105

5

8

0

13

0,0029

135

36

26

374

7,6123

0,45679

10

Giljušić Lea
(OK Marina Kaštela)

9

34

11

18

2

103

0,0085

8

19

1

36

0,0052

74

19

16

196

6,7653

0,43641

11

Bečić Mirna
(ŽOK Enna Vukovar)

1

4

2

1

0

13

0,0109

2

1

0

3

0,0109

14

4

3

42

0,6667

0,43507

12

Vukasović Stela
(OK Marina Kaštela)

2

7

1

2

1

26

0,0063

6

5

0

13

0,019

24

3

3

65

1,9385

0,40946

13

Bošnjak Tonka
(HAOK Mladost (Ž))

16

29

7

10

2

61

0,0039

7

15

1

26

0,0031

51

10

6

136

7,4632

0,39527

14

Jureta Klara
(OK Brda)

1

4

1

2

0

14

0,0058

0

0

0

0

0

8

3

3

26

0,3077

0,37457

15

Miloloža Karla
(OK Nebo)

10

21

4

4

1

41

0,0031

0

4

0

5

0

27

10

7

74

2,8378

0,36191

16

Ergović Ana
(OK Split (Ž))

14

27

9

4

0

45

0,0044

1

2

0

7

0,0005

12

4

5

45

1,8

0,36066

17

Vasilj Ivana
(ŽOK Ribola Kaštela)

5

9

2

3

1

12

0,0037

0

0

0

0

0

4

1

2

14

0,6429

0,35413

18

Jelić Laura
(OK Brda)

18

40

7

6

1

89

0,0028

2

5

0

8

0,0007

19

17

8

91

-2,6374

0,34751

19

Gajić Tatjana
(ŽOK Osijek)

1

4

0

0

0

12

0

1

2

0

3

0,0057

9

1

3

36

0,5556

0,33181

20

Kolobarić Karla
(ŽOK Ribola Kaštela)

8

18

0

4

1

35

0,0007

2

0

0

2

0,0014

13

5

3

53

1,6981

0,33036

21

Jakić Nina
(OK Don Bosco)

8

13

0

2

0

10

0

2

1

0

4

0,0015

6

0

1

18

3,6111

0,32468

22

Vlašić Ema
(OK Kelteks (Ž))

8

12

3

1

2

11

0,0038

0

1

0

2

0

2

2

1

11

-1,0909

0,32305

23

Perić Antea
(OK Dinamo)

3

4

0

0

0

0

0

0

1

0

1

0

1

0

3

8

-1

0,32305

24

Smojver Lorena
(OK Dinamo)

2

2

0

0

0

3

0

0

0

0

0

0

0

0

0

0

0

0,32305

25

Vekić Mateja
(HAOK Rijeka CO)

1

1

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0,32305

26

Čaić Marija
(OK Brda)

1

1

0

0

0

0

0

0

0

0

0

0

1

0

0

1

1

0,32305

27

Draganić Strgačić Roza
(OK Split (Ž))

1

1

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0,32305

Ranking Calculation

Opposite

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:  3

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