Ligue A Féminine

Competition

Ligue A Féminine Best players OPPOSITE
JoueursJouésServeServeBLKBLKAttaqueAttaqueRanking
  MS#=/TotSv ind.Sv ind.#=/TotBl ind.Bl ind.#=/TotSp ind.Sp ind.Index

1

MOMA BASSOKO Laetitia
(MULHOUSE)

22

81

36

51

26

337

0,0175

0,0175

10

27

9

85

0,0028

0,0028

344

59

45

699

27,8112

27,8112

0,62154

2

GICQUEL Lucille
(NANTES)

20

68

23

28

16

249

0,0126

0,0126

33

30

4

71

0,0107

0,0107

227

50

30

508

19,6772

19,6772

0,54719

3

GOLIAT Karolina
(MARCQ-EN-BAROEUL)

24

78

25

36

17

311

0,0111

0,0111

34

20

3

61

0,009

0,009

288

65

43

768

18,2812

18,2812

0,52374

4

SEGOVIA Dayana
(BÉZIERS)

22

78

17

19

21

249

0,01

0,01

24

20

5

58

0,0063

0,0063

202

41

29

502

20,51

20,51

0,52132

5

DAVIDOVIC Lara
(SAINT-RAPHAËL)

24

80

16

32

19

275

0,0093

0,0093

24

21

6

67

0,0064

0,0064

211

51

41

590

16,1356

16,1356

0,49214

6

TCHOUDJANG NANA Christelle
(CHAMALIÈRES)

24

86

15

22

11

288

0,0067

0,0067

27

35

4

72

0,0069

0,0069

300

72

49

770

19,9922

19,9922

0,48802

7

KREUTZ-DIOUCK Fatou Niane
(CANNES)

23

81

11

27

9

250

0,0051

0,0051

28

11

1

51

0,0072

0,0072

268

43

53

654

21,3028

21,3028

0,4802

8

SALKUTE Monika
(PAYS D'AIX VENELLES)

23

87

9

23

17

283

0,0068

0,0068

15

10

6

38

0,0039

0,0039

272

59

48

786

18,2634

18,2634

0,47634

9

MIMS Taylor
(VANDOEUVRE NANCY)

20

65

11

19

7

166

0,0057

0,0057

15

5

3

31

0,0047

0,0047

181

39

24

475

16,1474

16,1474

0,45639

10

DASCALU Alexandra
(PARIS SAINT-CLOUD)

10

32

10

18

7

103

0,0121

0,0121

10

16

4

38

0,0071

0,0071

93

34

25

309

3,521

3,521

0,4559

11

SZCZUROWSKA Julia
(CANNES)

8

23

10

16

8

60

0,0132

0,0132

4

1

1

6

0,0029

0,0029

29

5

4

68

6,7647

6,7647

0,4433

12

KAVALENKA Julia
(TERVILLE FLORANGE)

21

63

14

37

7

163

0,0058

0,0058

20

14

6

46

0,0056

0,0056

187

53

43

513

11,1754

11,1754

0,43419

13

LACERDA PEREIRA Heloiza
(MOUGINS)

20

61

10

18

8

146

0,0059

0,0059

16

18

0

35

0,0052

0,0052

195

54

40

561

10,9822

10,9822

0,43331

14

HOLLAS Eliise
(TERVILLE FLORANGE)

4

12

2

2

4

29

0,0085

0,0085

5

0

0

5

0,0071

0,0071

21

4

3

59

2,8475

2,8475

0,41967

15

ROTAR Amélie
(FRANCE AVENIR 2024)

15

42

4

19

5

118

0,0045

0,0045

11

3

4

22

0,0055

0,0055

108

12

20

319

10,0063

10,0063

0,41582

16

BETTENDORF Martenne
(VANDOEUVRE NANCY)

21

55

4

15

4

78

0,0024

0,0024

8

7

1

23

0,0024

0,0024

108

27

17

302

11,6556

11,6556

0,40097

17

ADIANA Estelle
(CHAMALIÈRES)

13

39

9

10

0

74

0,004

0,004

3

6

0

9

0,0013

0,0013

53

16

9

145

7,531

7,531

0,39435

18

ARBOS LISA
(MOUGINS)

3

7

2

3

0

16

0,0048

0,0048

0

1

0

1

0

0

15

5

3

41

1,1951

1,1951

0,36958

19

LAZAREVA Anna
(LE CANNET)

3

13

0

5

1

39

0,0018

0,0018

3

2

0

8

0,0055

0,0055

58

10

5

137

4,0803

4,0803

0,36328

20

DIOUF Guewe
(FRANCE AVENIR 2024)

5

12

1

7

1

29

0,0033

0,0033

1

0

0

1

0,0016

0,0016

32

17

7

107

0,8972

0,8972

0,35688

21

EBATOMBO Aurélia
(MULHOUSE)

7

10

1

4

0

12

0,0009

0,0009

3

4

1

8

0,0028

0,0028

18

6

3

42

2,1429

2,1429

0,34364

Calcul du classement

Pointu

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:  3

Serve

  • # serve ace

  • / half point

  • = serve error

Attaque

  • # point

  • / blocked

  • = error

BLK

  • # point

  • / invasion

  • = hand out

Filters applied

  • Minimum number of Matches played:  3