Optibet Latvijas Čempionāts 21/22

Optibet Latvijas Čempionāts 21/22

Optibet Latvijas Čempionāts 21/22 Best players OPPOSITE
PlayerPlayedServeServeBlockBlockAttackAttackRanking
  MS#=/TotSv ind.Sv ind.#=/TotBl ind.Bl ind.#=/TotSp ind.Sp ind.Index

1

Andersons Dāvis
(Kuldīgas NSS)

1

3

1

2

3

12

0,0301

0,0301

1

0

0

1

0,0075

0,0075

11

1

5

24

0,625

0,625

0,46607

2

Kaverskis Kaspars
(Vecumnieki)

17

66

11

29

3

232

0,0047

0,0047

29

7

0

45

0,0096

0,0096

155

45

18

331

18,3444

18,3444

0,41643

3

Jemeļjanovs Pāvels
(Jēkabpils Lūši)

6

21

12

19

0

80

0,0132

0,0132

11

14

0

33

0,0121

0,0121

71

25

15

154

4,2273

4,2273

0,41183

4

Mucenieks Kristers
(Aizpute)

16

57

5

21

1

177

0,0021

0,0021

17

6

0

33

0,0061

0,0061

171

47

21

370

15,8676

15,8676

0,37035

5

Getman Nazar
(Daugavpils Universitāte/Ezerzeme)

6

21

8

16

5

68

0,0134

0,0134

3

7

0

13

0,0031

0,0031

62

19

6

135

5,7556

5,7556

0,36982

6

Gabduļins Matīss
(RTU/Robežsardze/Jūrmala)

6

22

2

13

2

78

0,004

0,004

11

29

0

53

0,0109

0,0109

103

7

19

244

6,9426

6,9426

0,36562

7

Kalniņš Toms
(Rīgas Tehniskā Universitāte)

7

22

5

17

0

64

0,0041

0,0041

14

3

0

20

0,0114

0,0114

62

28

15

157

2,6624

2,6624

0,34979

8

Vilcāns Sandis
(VK Biolars/Jelgava MSĢ)

6

23

7

21

0

69

0,0073

0,0073

6

9

0

19

0,0063

0,0063

77

21

20

174

4,7586

4,7586

0,34894

9

Muižnieks Jānis
(Rīgas Tehniskā Universitāte)

6

20

1

7

3

91

0,0037

0,0037

8

0

0

10

0,0074

0,0074

42

14

3

89

5,618

5,618

0,33949

10

Žolnerovičs Devids
(Daugavpils Universitāte/Ezerzeme)

4

16

1

7

0

52

0,0014

0,0014

5

0

0

7

0,0069

0,0069

47

10

5

63

8,127

8,127

0,3359

11

Cīrulis Fēlikss
(Kuldīgas NSS)

12

44

9

32

4

139

0,0063

0,0063

10

9

2

25

0,0048

0,0048

124

60

32

331

4,2538

4,2538

0,33337

12

Ekhards Jēkabs
(VK Ozolnieki)

15

46

7

17

1

129

0,0032

0,0032

7

3

0

24

0,0028

0,0028

105

29

26

280

8,2143

8,2143

0,32401

13

Šepte Kristaps
(VK Ventspils)

11

28

5

12

3

59

0,0043

0,0043

5

9

0

22

0,0027

0,0027

53

32

8

142

2,5634

2,5634

0,30516

14

Keišs Zigmārs
(VK Ozolnieki)

1

3

0

0

0

9

0

0

1

0

0

7

0,007

0,007

11

1

4

22

0,8182

0,8182

0,29786

15

Kudrovskis Ralfs
(Kuldīgas NSS)

1

1

0

0

0

2

0

0

1

0

0

2

0,0075

0,0075

1

0

0

1

1

1

0,2968

16

Puķītis Rihards
(Daugavpils Universitāte/Ezerzeme)

3

6

0

1

1

11

0,0018

0,0018

2

0

0

3

0,0036

0,0036

4

3

0

11

0,5455

0,5455

0,28626

17

Strautnieks Ēriks
(VK Ozolnieki)

16

32

0

10

0

42

0

0

3

2

0

12

0,0011

0,0011

40

14

13

109

3,8165

3,8165

0,28112

18

Liepa Toms Emīls
(VK Biolars/Jelgava MSĢ)

16

26

3

12

0

44

0,0011

0,0011

6

0

0

8

0,0023

0,0023

22

16

3

62

1,2581

1,2581

0,27719

19

Landzāns Kristers
(Jēkabpils Lūši)

2

3

1

0

0

1

0,0034

0,0034

1

0

0

1

0,0034

0,0034

4

0

0

6

2

2

0,27685

20

Caune Rūdis
(Rīgas Volejbola skola)

8

11

2

4

0

14

0,0017

0,0017

0

0

0

0

0

0

1

3

0

13

-1,6923

-1,6923

0,26914

21

Lindbergs Rihards
(Rīgas Volejbola skola)

5

10

1

5

0

15

0,0016

0,0016

0

0

0

1

0

0

4

6

4

23

-2,6087

-2,6087

0,26847

22

Cvilikovskis Kristaps
(Augšdaugava)

2

5

0

2

0

6

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0,2612

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

  • #NOME?

Attack

  • # point

  • / blocked

  • #NOME?

Block

  • # point

  • / Net touch

  • #NOME?

Filters applied

  • Minimum number of Matches played:  1