Elme Messer Women`s Baltic League 25/26

Elme Messer Women`s Baltic League 25/26

Elme Messer Women`s Baltic League 25/26 Best players OPPOSITE
PlayerPlayedServeServeBlockBlockAttackAttackRanking
  MS#=/TotSv ind.Sv ind.#=/TotBl ind.Bl ind.#=/TotSp ind.Sp ind.Index

1

Zariņa Katrīna Laura
(Riga Volleyball School/LU)

11

41

24

26

12

151

0.0198

0.0198

11

4

0

22

0.0061

0.0061

3

0

1

12

6.8333

6.8333

0.50995

2

Tammel Kairin
(TÜ/Bigbank)

12

45

17

29

8

148

0.0128

0.0128

10

13

1

42

0.0051

0.0051

95

25

19

278

8.2554

8.2554

0.48366

3

Vytulytė Eglė
(LTU U18)

13

47

15

7

12

140

0.0132

0.0132

11

11

2

30

0.0054

0.0054

91

36

17

300

5.9533

5.9533

0.47628

4

Paukštytė Martyna
(Kaunas-VDU)

14

47

14

14

3

153

0.0084

0.0084

17

22

0

56

0.0084

0.0084

172

42

23

414

12.1473

12.1473

0.46648

5

Suvi Ingris
(TÜ/Bigbank)

13

49

10

28

8

129

0.0085

0.0085

9

7

0

27

0.0042

0.0042

126

27

15

325

12.6646

12.6646

0.46439

6

Čelnova Anete
(Riga Volleyball School/LU)

13

46

16

17

7

115

0.0106

0.0106

10

20

1

51

0.0046

0.0046

98

46

16

280

5.9143

5.9143

0.45114

7

Krustkalne Katrina Paula
(Riga Volleyball School/LU)

13

38

11

6

8

72

0.0088

0.0088

12

9

0

32

0.0055

0.0055

40

16

9

121

4.7107

4.7107

0.4291

8

Kundelyte Juta
(LTU U18)

11

33

17

28

0

90

0.0099

0.0099

6

18

0

39

0.0035

0.0035

73

39

17

194

2.8918

2.8918

0.42772

9

Kulikauskaite Ugne
(VMSM Sostinės tauras - VTC)

13

32

12

14

3

80

0.0071

0.0071

6

16

1

32

0.0028

0.0028

37

12

11

144

3.1111

3.1111

0.40284

10

Allorg Kristel
(Rae Spordikool/VIASTON)

1

3

0

2

1

9

0.0078

0.0078

0

2

0

2

0

0

7

1

0

11

1.6364

1.6364

0.39798

11

Tugedam Karmen
(Audentese SG)

10

38

8

28

1

76

0.0055

0.0055

15

12

0

43

0.0092

0.0092

83

41

20

254

3.2913

3.2913

0.39681

12

Jociūtė Nida
(LTU U18)

11

30

7

9

1

63

0.0046

0.0046

13

3

0

17

0.0074

0.0074

56

23

10

154

4.4805

4.4805

0.39194

13

Vahula Heidi
(Audentese SG)

12

33

7

4

2

62

0.0046

0.0046

1

5

0

12

0.0005

0.0005

55

16

17

153

4.7451

4.7451

0.38561

14

Bartkute Vakare
(Kaunas-VDU)

14

29

8

14

0

47

0.004

0.004

3

2

1

7

0.0015

0.0015

30

7

6

72

6.8472

6.8472

0.35827

15

Mandel Karmen
(Audentese SG)

2

2

1

1

0

3

0.003

0.003

0

0

0

0

0

0

0

0

0

0

0

0

0.34841

16

Ketlere Katrina
(RSU)

13

41

2

9

1

46

0.0015

0.0015

6

14

4

48

0.0031

0.0031

48

28

22

224

-0.3661

-0.3661

0.33773

17

Rahuoja Ragne
(Rae Spordikool/VIASTON)

1

1

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0.32305

18

Petkutė Urtė
(LTU U18)

1

1

0

0

0

0

0

0

0

1

0

1

0

0

1

1

1

3

-0.3333

-0.3333

0.32158

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