MEVZA League Men 2025/2026

MEVZA League Men 2025/2026

MEVZA League Men 2025/2026 Best players MIDDLE BLOCKER
PlayerPlayedBlockBlockServeServeAttackAttackRanking
  MS#=/TotBl ind.Bl ind.#=/TotSv ind.Sv ind.#=/TotSp ind.Sp ind.Index

1

EKE Péter
(MAV Elore-Foxconn (HUN))

2

7

15

14

1

36

0.043

0.043

2

1

0

17

0.0057

0.0057

7

2

0

11

3.1818

3.1818

0.59946

2

SINĐELIĆ Marko
(OK BUDUĆNOST (MNE))

6

23

29

33

0

85

0.0273

0.0273

3

7

1

81

0.0038

0.0038

33

4

5

62

8.9032

8.9032

0.50731

3

BABIĆ Luka
(OK BUDVA (MNE))

4

16

15

18

1

44

0.0209

0.0209

4

2

3

62

0.0098

0.0098

9

0

4

22

3.6364

3.6364

0.49044

4

JAKOPEC Sven
(HAOK Mladost ZAGREB m (CRO))

4

12

14

8

0

24

0.021

0.021

3

0

1

38

0.006

0.006

20

0

1

29

7.8621

7.8621

0.47925

5

LUNA SLAIBE Karim Alejandro
(MAV Elore-Foxconn (HUN))

2

8

9

10

4

35

0.0258

0.0258

0

2

0

24

0

0

14

1

0

23

4.5217

4.5217

0.47202

6

PERIĆ Stipe
(HAOK Mladost ZAGREB m (CRO))

4

15

13

13

0

33

0.0195

0.0195

4

2

0

70

0.006

0.006

13

3

3

29

3.6207

3.6207

0.46313

7

SABLATNIG Sebastian
(SK Zadruga AICH/DOB (AUT))

3

10

8

6

0

31

0.0176

0.0176

1

0

1

47

0.0044

0.0044

18

0

0

27

6.6667

6.6667

0.44884

8

PETROVIĆ Srđan
(OK BUDUĆNOST (MNE))

6

22

13

20

0

43

0.0122

0.0122

0

5

6

74

0.0056

0.0056

18

1

2

31

10.6452

10.6452

0.43031

9

JANKOVIĆ Stefan
(MOK Mursa Osijek (CRO))

4

12

11

5

0

17

0.0163

0.0163

1

7

1

39

0.003

0.003

10

5

2

26

1.3846

1.3846

0.42524

10

ŠUNJO Gabriel
(MOK Mursa Osijek (CRO))

3

10

7

6

0

14

0.0141

0.0141

0

6

2

40

0.004

0.004

13

3

1

26

3.4615

3.4615

0.42136

11

ĆINĆUR Matija
(OK BUDVA (MNE))

4

16

10

21

1

43

0.014

0.014

1

8

1

57

0.0028

0.0028

16

2

7

33

3.3939

3.3939

0.41438

12

ĐUROVIĆ Nikola
(HAOK Mladost ZAGREB m (CRO))

1

4

3

9

0

12

0.0164

0.0164

0

1

0

13

0

0

5

1

2

11

0.7273

0.7273

0.41049

13

VODUŠEK Timotej
(OK i-Vent MARIBOR)

6

22

6

24

0

46

0.006

0.006

5

14

1

82

0.006

0.006

15

2

3

37

5.9459

5.9459

0.38868

14

UREMOVIČ Filip
(OK i-Vent MARIBOR)

6

19

9

18

0

36

0.0091

0.0091

1

8

2

53

0.003

0.003

10

1

4

24

3.9583

3.9583

0.38825

15

GRGIĆ Matko
(MOK Mursa Osijek (CRO))

1

4

2

8

0

10

0.0111

0.0111

0

1

0

11

0

0

1

0

0

2

2

2

0.37922

16

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

3

8

4

8

0

26

0.0088

0.0088

0

4

0

25

0

0

14

1

2

20

4.4

4.4

0.37327

17

AMBRUS Bence
(MAV Elore-Foxconn (HUN))

1

2

1

3

0

6

0.0055

0.0055

0

0

0

7

0

0

0

0

0

0

0

0

0.34823

18

REINSTADLER Tobias
(SK Zadruga AICH/DOB (AUT))

3

7

0

2

0

3

0

0

1

1

1

22

0.0044

0.0044

4

0

0

5

5.6

5.6

0.33848

19

DEŽMAN Tai
(OK i-Vent MARIBOR)

6

11

1

2

0

3

0.001

0.001

2

1

0

21

0.002

0.002

0

0

1

3

-3.6667

-3.6667

0.33321

20

BREZNIK Jakob
(OK i-Vent MARIBOR)

3

4

0

0

0

0

0

0

0

2

0

2

0

0

2

0

0

2

4

4

0.31911

21

ČELEBIĆ Vukota
(OK BUDVA (MNE))

1

2

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

1

2

2

0.31911

22

KONATAR Uroš
(OK BUDUĆNOST (MNE))

1

1

0

1

0

1

0

0

0

1

0

1

0

0

0

0

0

0

0

0

0.31911

23

LEČIĆ Dalibor
(OK BUDVA (MNE))

1

1

0

0

0

0

0

0

0

0

0

2

0

0

0

0

1

1

-1

-1

0.31764

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