Volleyball League Women 2017/2018

Playoff 4th Final + Playout 9-10

Volleyball League Women 2017/2018 Best players MIDDLE BLOCKER
PlayerPlayedServeServeBlockBlockAttackAttackRanking
  MS#=/TotSv ind.Sv ind.#=/TotBl ind.Bl ind.#=/TotSp ind.Sp ind.Index

1

Holaskova Katerina
(VC Kanti Schaffhausen)

3

14

5

6

3

54

0.0136

0.0136

19

17

0

43

0.0323

0.0323

29

8

6

70

3

3

0.65988

2

Moffett Sabel
(TS Volley Düdingen)

2

6

6

3

0

29

0.024

0.024

4

5

0

14

0.016

0.016

13

2

0

21

3.1429

3.1429

0.64729

3

White Jazmine
(Sm'Aesch Pfeffingen)

2

7

4

1

2

23

0.0199

0.0199

4

9

0

24

0.0133

0.0133

16

1

1

25

3.92

3.92

0.59779

4

Lazarenko Angelina
(Volero Zürich)

1

3

2

2

0

10

0.015

0.015

2

4

0

9

0.015

0.015

10

1

1

14

1.7143

1.7143

0.56228

5

Alons Johanna Willemina
(KULAchange VBC Galina)

2

7

1

0

2

16

0.01

0.01

6

11

0

21

0.0199

0.0199

6

4

1

21

0.3333

0.3333

0.5468

6

Schottroff Gabi
(Volero Zürich)

1

3

2

1

0

10

0.015

0.015

1

0

0

6

0.0075

0.0075

2

0

0

3

2

2

0.51355

7

Halter Martina
(Viteos NUC)

3

14

4

2

1

44

0.0085

0.0085

9

5

0

17

0.0153

0.0153

13

1

4

29

3.8621

3.8621

0.50983

8

Becker Kerley
(TS Volley Düdingen)

2

6

0

3

2

23

0.008

0.008

2

4

0

13

0.008

0.008

21

4

0

31

3.2903

3.2903

0.45644

9

Zaloznik valentina
(Hôtel Christal VFM)

1

3

1

1

0

7

0.0075

0.0075

1

2

0

7

0.0075

0.0075

9

2

2

20

0.75

0.75

0.44419

10

Lutz Nina
(VC Kanti Schaffhausen)

3

14

4

0

0

46

0.0068

0.0068

5

6

0

16

0.0085

0.0085

7

4

2

21

0.6667

0.6667

0.44393

11

Matter Madlaina
(Sm'Aesch Pfeffingen)

2

7

1

3

1

25

0.0066

0.0066

1

5

0

11

0.0033

0.0033

5

1

0

10

2.8

2.8

0.4133

12

Bigger Kathia
(KULAchange VBC Galina)

2

7

1

0

1

21

0.0066

0.0066

1

5

0

10

0.0033

0.0033

1

1

1

10

-0.7

-0.7

0.40677

13

Fanelli Ilaria
(Volley Lugano)

2

6

1

1

1

9

0.008

0.008

0

3

1

6

0

0

6

2

0

14

1.7143

1.7143

0.40181

14

Borelli Francesca
(Volley Lugano)

2

6

0

0

1

8

0.004

0.004

1

3

0

6

0.004

0.004

7

1

2

17

1.4118

1.4118

0.39229

15

Girard Ségolène
(Viteos NUC)

3

14

2

5

0

42

0.0034

0.0034

3

8

0

18

0.0051

0.0051

12

5

7

39

0

0

0.39143

16

Torterolo Larissa
(Volley Lugano)

2

5

1

2

0

9

0.004

0.004

1

3

1

5

0.004

0.004

0

0

0

0

0

0

0.3897

17

Smiljkovic Marija
(Volley Top Luzern)

3

8

1

4

0

25

0.0017

0.0017

3

3

0

11

0.0051

0.0051

0

1

0

4

-2

-2

0.37707

18

Galic Tamara
(Volley Lugano)

2

2

1

0

0

3

0.004

0.004

0

0

0

0

0

0

0

0

0

0

0

0

0.36491

19

Werfeli Lea
(Sm'Aesch Pfeffingen)

2

2

1

1

0

6

0.0033

0.0033

0

2

0

3

0

0

1

0

0

2

1

1

0.36109

20

Staffelbach Xenia
(Viteos NUC)

3

5

1

0

0

7

0.0017

0.0017

1

0

0

1

0.0017

0.0017

0

1

0

1

-5

-5

0.35627

21

Lopes Da Silva Nuria
(KULAchange VBC Galina)

2

7

0

1

0

3

0

0

1

2

0

5

0.0033

0.0033

5

1

2

15

0.9333

0.9333

0.35384

22

Florin Janina
(KULAchange VBC Galina)

1

3

0

0

0

5

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0.33246

23

Vuilleumier Julie
(Hôtel Christal VFM)

1

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0.33246

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