Cronimet League 23/24

Cronimet League 23/24

Cronimet League 23/24 Best players OPPOSITE
PlayerPlayedServeServeBlockBlockAttackAttackRanking
  MS#=/TotSv ind.Sv ind.#=/TotBl ind.Bl ind.#=/TotSp ind.Sp ind.Index

1

Svans Toms
(PÄRNU VK)

23

82

36

66

19

349

0.0144

0.0144

33

71

2

175

0.0086

0.0086

159

26

20

294

31.517

31.517

0.53281

2

Santos Renato Oliveira
(Barrus Võru VK)

22

84

32

83

14

301

0.0121

0.0121

33

43

1

118

0.0087

0.0087

435

87

72

844

27.4692

27.4692

0.49951

3

Aubrey Matthew
(Selver/TalTech)

23

81

41

60

23

348

0.017

0.017

38

57

5

149

0.0101

0.0101

244

49

54

584

19.5565

19.5565

0.49719

4

Teppan Renee
(PÄRNU VK)

15

54

22

47

16

207

0.0157

0.0157

24

33

0

95

0.0099

0.0099

203

41

44

430

14.8186

14.8186

0.4649

5

Širjakovs Andris
(BIGBANK Tartu)

15

57

6

42

11

167

0.0065

0.0065

26

44

0

94

0.0099

0.0099

176

31

21

394

17.9391

17.9391

0.42617

6

Gabdulļins Matīss
(RTU Robežsardze/Jūrmala)

22

76

10

22

7

223

0.0045

0.0045

23

25

0

77

0.0061

0.0061

256

30

59

676

18.7751

18.7751

0.39742

7

Veloso Matheus Araujo
(Amber Volley)

18

63

7

35

4

203

0.0039

0.0039

22

36

0

80

0.0077

0.0077

231

65

42

515

15.1689

15.1689

0.38587

8

Makarov Ilija
(Ezerzeme/DU)

22

68

15

55

11

202

0.0075

0.0075

17

57

0

126

0.0049

0.0049

176

41

57

404

13.1287

13.1287

0.38081

9

Täht Tarvo
(Barrus Võru VK)

14

44

14

36

7

120

0.0089

0.0089

28

33

0

93

0.0118

0.0118

51

9

6

98

16.1633

16.1633

0.36599

10

Rantanen Siim Olavi
(PÄRNU VK)

11

29

6

14

6

77

0.0062

0.0062

10

23

0

46

0.0052

0.0052

63

13

9

148

8.0338

8.0338

0.35224

11

Vilcāns Sandis
(Ezerzeme/DU)

24

68

6

19

10

112

0.0041

0.0041

23

51

0

117

0.0059

0.0059

109

34

44

290

7.269

7.269

0.34132

12

Katinas Daumantas
(Amber Volley)

18

51

8

32

5

152

0.0045

0.0045

9

31

0

59

0.0031

0.0031

81

23

26

254

6.4252

6.4252

0.32445

13

Landzāns Kristers
(Jēkabpils Lūši)

14

43

6

21

1

80

0.0027

0.0027

10

32

0

52

0.0039

0.0039

71

33

23

214

3.014

3.014

0.3053

14

Kalnins Toms
(RTU Robežsardze/Jūrmala)

23

69

9

33

1

98

0.0025

0.0025

10

15

1

54

0.0025

0.0025

74

19

24

199

10.7487

10.7487

0.28474

15

Üprus Jan Markus
(Selver/TalTech)

20

42

5

5

6

69

0.0033

0.0033

4

7

1

16

0.0012

0.0012

39

9

12

90

8.4

8.4

0.28227

16

Jakobson Karl
(Barrus Võru VK)

8

12

0

5

0

15

0

0

0

2

0

4

0

0

5

1

3

17

0.7059

0.7059

0.2612

17

Timusk Kaspar
(PÄRNU VK)

1

4

0

2

0

4

0

0

0

0

0

0

0

0

2

1

1

4

0

0

0.2612

18

Galdikas Laurynas
(Amber Volley)

2

2

0

0

0

1

0

0

0

0

0

0

0

0

1

0

0

3

0.6667

0.6667

0.2612

19

Hansman Hergo
(BIGBANK Tartu)

5

10

0

9

0

19

0

0

0

4

0

4

0

0

9

8

5

36

-1.1111

-1.1111

0.25696

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