Ligue A Féminine 22-23

Play-Offs LAF

Ligue A Féminine 22-23 Best players MIDDLE BLOCKER
JoueursJouésServeServeBLKBLKAttaqueAttaqueRanking
  MS#=/TotSv ind.Sv ind.#=/TotBl ind.Bl ind.#=/TotSp ind.Sp ind.Index

1

KOCHURINA Elizaveta
(LE CANNET)

8

33

10

22

4

70

0,0099

0,0099

30

33

3

109

0,0211

0,0211

75

8

6

139

14,482

14,482

0,58028

2

THATER Emily
(PARIS ST CLOUD)

3

14

4

3

3

45

0,012

0,012

12

13

0

32

0,0206

0,0206

18

9

2

44

2,2273

2,2273

0,57299

3

KEENE Jaelyn
(NANTES)

3

13

6

2

3

37

0,0166

0,0166

7

14

0

38

0,0129

0,0129

23

3

6

46

3,9565

3,9565

0,56611

4

SAMADAN Martina
(NANTES)

3

13

2

6

5

50

0,0129

0,0129

7

20

0

40

0,0129

0,0129

18

3

1

37

4,9189

4,9189

0,53539

5

BAUER Christina
(PAYS D'AIX VENELLES)

6

26

3

4

6

77

0,0082

0,0082

19

28

0

71

0,0174

0,0174

35

1

4

85

9,1765

9,1765

0,53165

6

NGOLONGOLO Naomi
(PARIS ST CLOUD)

3

14

1

9

5

54

0,0103

0,0103

9

10

0

23

0,0155

0,0155

15

2

2

38

4,0526

4,0526

0,52765

7

OGOMS Alicia
(TERVILLE-FLORANGE)

2

5

1

0

1

20

0,0056

0,0056

7

3

0

12

0,0196

0,0196

11

2

0

24

1,875

1,875

0,50826

8

OLINGA ANDELA Leandra
(MULHOUSE)

6

22

1

4

4

88

0,005

0,005

18

13

8

67

0,018

0,018

22

2

1

47

8,8936

8,8936

0,50631

9

VAN AVERMAET Silke
(MULHOUSE)

6

21

4

11

4

60

0,008

0,008

13

13

5

68

0,013

0,013

38

6

6

86

6,3488

6,3488

0,49522

10

FARRIOL Bianca
(BEZIERS)

4

14

0

4

3

53

0,0044

0,0044

11

19

5

64

0,016

0,016

15

2

3

36

3,8889

3,8889

0,4779

11

TRACH Olga
(PAYS D'AIX VENELLES)

6

26

0

9

5

72

0,0046

0,0046

12

21

0

60

0,011

0,011

34

5

5

92

6,7826

6,7826

0,45226

12

FELIX Claire
(CANNES)

2

7

1

2

1

20

0,0066

0,0066

2

5

4

13

0,0066

0,0066

10

1

0

23

2,7391

2,7391

0,43359

13

GATES Madeleine
(CANNES)

2

7

1

5

0

21

0,0033

0,0033

3

2

7

21

0,0099

0,0099

15

2

1

32

2,625

2,625

0,42584

14

SIDIBE Mariam
(TERVILLE-FLORANGE)

2

7

1

1

1

28

0,0056

0,0056

2

2

0

10

0,0056

0,0056

18

2

4

30

2,8

2,8

0,41863

15

MAYER Chloe
(LE CANNET)

4

16

3

5

1

60

0,0053

0,0053

4

6

3

25

0,0053

0,0053

9

3

2

25

2,56

2,56

0,41393

16

MEDEIROS Milka Marcilias
(LE CANNET)

7

21

2

2

3

53

0,0039

0,0039

5

12

2

46

0,0039

0,0039

24

5

3

54

6,2222

6,2222

0,39937

17

MOHLER Blake
(BEZIERS)

4

14

0

1

1

20

0,0015

0,0015

5

14

2

33

0,0073

0,0073

19

2

2

41

5,122

5,122

0,39808

18

PARADZIK Ajla
(MULHOUSE)

3

5

1

1

1

12

0,0041

0,0041

2

1

1

8

0,0041

0,0041

4

0

0

9

2,2222

2,2222

0,395

19

DIA Aminata
(TERVILLE-FLORANGE)

1

2

0

0

0

7

0

0

1

2

0

6

0,007

0,007

1

0

0

5

0,4

0,4

0,37563

20

STANIULYTE Ruta
(LE CANNET)

2

4

1

2

0

11

0,0028

0,0028

1

4

0

8

0,0028

0,0028

2

0

0

5

1,6

1,6

0,37514

21

ANDRIAMAHERIZO Marie-Raphaëlle
(CANNES)

2

5

0

0

1

9

0,0033

0,0033

0

0

0

0

0

0

1

0

0

2

2,5

2,5

0,35904

22

SAGER-WEIDER Isaline
(NANTES)

2

4

0

0

0

4

0

0

0

1

1

5

0

0

0

0

0

3

0

0

0,33246

23

LEGRAND Nora
(NANTES)

2

2

0

1

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0,33246

Calcul du classement

Central

Le classement prend en compte :

  • 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

Attaque

  • # point

  • / blocked

  • = error

BLK

  • # point

  • / invasion

  • = hand out

Filters applied

  • Minimum number of Matches played:  1