TOP SPORT Lietuvos Moterų Tinklinio Čempionatas 2022/2023

Reguliarusis Čempionatas

TOP SPORT Lietuvos Moterų Tinklinio Čempionatas 2022/2023 Best players MIDDLE BLOCKER
PlayerPlayedServeServeBlockBlockAttackAttackRanking
  MS#=/TotSv ind.Sv ind.#=/TotBl ind.Bl ind.#=/TotSp ind.Sp ind.Index

1

MUKAITĖ Emilija
(Jonavos SC)

8

29

8

12

0

86

0.0066

0.0066

26

9

0

47

0.0213

0.0213

23

4

3

55

8.4364

8.4364

0.54126

2

KASPARAVIČIŪTĖ Gabija
(TK “Kaunas”-VDU)

6

19

9

15

1

72

0.0128

0.0128

9

5

0

23

0.0115

0.0115

44

6

0

64

11.2812

11.2812

0.5376

3

FIRINOVIČ Lilija
(Svaja - Viktorija - LSU)

6

24

16

17

0

86

0.016

0.016

6

6

0

16

0.006

0.006

76

20

9

221

5.1041

5.1041

0.51866

4

KVEDARAITĖ Danielė
(JONAVOS "Aušrinė")

6

16

5

9

0

57

0.0074

0.0074

10

1

0

14

0.0147

0.0147

58

2

7

123

6.374

6.374

0.50098

5

SHRAMKO Marina
(JONAVOS "Aušrinė")

5

12

6

5

0

34

0.0108

0.0108

5

4

0

10

0.009

0.009

12

1

3

24

4

4

0.48864

6

KARVELYTĖ Aurėja
(JONAVOS "Aušrinė")

5

13

5

2

1

46

0.0106

0.0106

5

1

0

8

0.0088

0.0088

15

2

2

38

3.7632

3.7632

0.48572

7

GABULAITĖ Roberta
(Svaja - Viktorija - LSU)

8

30

7

5

3

92

0.008

0.008

10

10

0

31

0.008

0.008

35

7

3

74

10.1351

10.1351

0.46928

8

VALIONYTĖ Vaiva
(TK “Kaunas”-VDU)

6

17

6

5

2

57

0.0102

0.0102

4

1

0

12

0.0051

0.0051

27

4

0

44

8.8864

8.8864

0.46806

9

MOTIEJŪNAITĖ Kotryna
(TK “Kaunas”-VDU)

2

5

0

1

0

10

0

0

4

2

0

8

0.0169

0.0169

7

2

1

13

1.5385

1.5385

0.44033

10

MIKOLIŪNAITĖ Greta
(JONAVOS "Aušrinė")

5

13

4

2

0

52

0.0071

0.0071

3

3

0

10

0.0053

0.0053

18

5

0

43

3.9302

3.9302

0.43168

11

ŽUKAITĖ Austėja
(Svaja - Viktorija - LSU)

7

22

4

6

1

52

0.0048

0.0048

8

6

0

23

0.0076

0.0076

15

1

2

51

5.1765

5.1765

0.42901

12

KAČINAITĖ Neringa
(VILNIAUS Universitetas)

8

29

6

6

0

73

0.0045

0.0045

12

16

0

33

0.0091

0.0091

24

16

8

94

0

0

0.42648

13

ŠIGAUSKAITĖ Stela
(Svaja - Viktorija - LSU)

5

15

3

8

2

38

0.0063

0.0063

4

7

0

19

0.005

0.005

14

2

4

36

3.3333

3.3333

0.4224

14

IVANAUSKAITĖ Gelmė
(Jonavos SC)

7

21

4

7

0

44

0.0038

0.0038

8

13

0

29

0.0077

0.0077

1

2

1

20

-2.1

-2.1

0.41138

15

UMANTAITĖ Benita
(VILNIAUS Universitetas)

6

22

4

7

0

59

0.0044

0.0044

4

9

0

13

0.0044

0.0044

49

15

7

162

3.6667

3.6667

0.40278

16

GILYTĖ Ieva
(Jonavos SC)

5

14

4

8

0

39

0.0046

0.0046

4

4

0

8

0.0046

0.0046

4

6

1

28

-1.5

-1.5

0.39556

17

OBELIENIUTE Deimante
(VILNIAUS Universitetas)

6

15

4

5

0

45

0.0042

0.0042

0

5

0

8

0

0

11

4

1

37

2.4324

2.4324

0.3708

18

TOLIUŠYTĖ Gabija
(VILNIAUS Universitetas)

8

21

4

8

0

49

0.003

0.003

1

8

0

11

0.0008

0.0008

11

10

3

40

-1.05

-1.05

0.35954

19

ERGARDT Eva
(Jonavos SC)

2

3

0

3

0

3

0

0

1

0

0

1

0.0035

0.0035

0

0

0

0

0

0

0.35339

20

BLINSTRUBYTĖ Vestina
(VILNIAUS Universitetas)

1

2

0

1

0

4

0

0

0

1

0

3

0

0

1

1

1

5

-0.4

-0.4

0.33177

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