Coupe de France 2025

Coupe de France 2025 Féminine

Coupe de France 2025 Best players MIDDLE BLOCKER
JoueursJouésServeServeBLKBLKAttaqueAttaqueRanking
  MS#=/TotSv ind.Sv ind.#=/TotBl ind.Bl ind.#=/TotSp ind.Sp ind.Index

1

ELOUGA Eva-Brooklyn
(PAYS D'AIX VENELLES)

1

4

0

3

0

10

0

0

8

2

0

10

0,0471

0,0471

5

1

0

12

1,3333

1,3333

0,63532

2

NESIMOVIC Nina
(QUIMPER)

1

3

0

1

0

4

0

0

6

4

0

13

0,0451

0,0451

1

0

2

5

-0,6

-0,6

0,61983

3

KULIKOVA Tatiana
(TERVILLE FLORANGE)

1

5

1

1

2

13

0,0135

0,0135

5

0

5

16

0,0224

0,0224

8

3

1

14

1,4286

1,4286

0,59542

4

MASSUEL Camille
(CANNES)

1

4

0

3

2

11

0,0114

0,0114

3

1

2

16

0,017

0,017

6

3

1

18

0,4444

0,4444

0,54049

5

EBANGWESE SANTITA
(BORDEAUX MERIGNAC)

1

3

0

1

0

6

0

0

4

0

0

4

0,0294

0,0294

10

2

0

13

1,8462

1,8462

0,52332

6

KIROV Masa
(VOLERO LE CANNET)

1

3

3

1

0

11

0,0221

0,0221

0

0

0

0

0

0

1

2

1

6

-1

-1

0,52088

7

JORGENSEN AMALIE
(CANNES)

1

4

1

3

2

11

0,017

0,017

1

0

1

3

0,0057

0,0057

6

0

1

12

1,6667

1,6667

0,51872

8

FANGUEDOU Fatoumata
(CHAMALIERES)

1

3

1

2

0

8

0,0075

0,0075

2

2

0

7

0,015

0,015

2

0

0

3

2

2

0,49598

9

KOULISIANI Ela
(PAYS D'AIX VENELLES)

1

4

1

2

2

17

0,0176

0,0176

0

0

0

0

0

0

8

0

0

14

2,2857

2,2857

0,48781

10

GARCIA Clémence
(MARCQ EN BAROEUL)

1

5

2

1

0

14

0,009

0,009

2

0

2

10

0,009

0,009

1

1

1

6

-0,8333

-0,8333

0,46349

11

BUDRAK Katarina
(BORDEAUX MERIGNAC)

1

3

1

3

1

16

0,0147

0,0147

0

0

0

0

0

0

6

0

0

9

2

2

0,46106

12

BACON Karson
(TERVILLE FLORANGE)

1

5

0

3

1

13

0,0045

0,0045

3

0

2

16

0,0135

0,0135

6

3

1

14

0,7143

0,7143

0,45604

13

TONTAI ARISTEA
(MULHOUSE)

1

4

1

1

0

11

0,0057

0,0057

2

0

5

12

0,0114

0,0114

5

1

1

11

1,0909

1,0909

0,4537

14

KOTAR ULIANA
(MARCQ EN BAROEUL)

1

5

1

3

0

14

0,0045

0,0045

2

1

2

8

0,009

0,009

9

0

1

17

2,3529

2,3529

0,42997

15

STOCKMAN Marissa
(BEZIERS)

1

4

1

0

0

11

0,0059

0,0059

1

1

0

2

0,0059

0,0059

2

0

3

9

-0,4444

-0,4444

0,41701

16

MOORE Amelia
(BEZIERS)

1

3

0

3

0

4

0

0

2

0

0

2

0,0118

0,0118

8

1

0

9

2,3333

2,3333

0,40888

17

LOUESSARD Manon
(TERVILLE FLORANGE)

1

4

2

2

0

8

0,009

0,009

0

0

0

0

0

0

0

0

0

0

0

0

0,40696

18

MELIUSHKYNA Diana
(QUIMPER)

1

3

0

1

0

14

0

0

1

7

0

13

0,0075

0,0075

12

2

1

20

1,35

1,35

0,38031

19

LOFF DA SILVA Raquel
(CHAMALIERES)

1

3

0

3

0

10

0

0

1

4

0

7

0,0075

0,0075

4

1

1

11

0,5455

0,5455

0,37884

20

KNEIFLOVA EMA
(MARCQ EN BAROEUL)

1

2

0

0

0

3

0

0

0

0

3

5

0

0

2

1

0

5

0,4

0,4

0,33314

21

PLAT Constance
(BORDEAUX MERIGNAC)

1

3

0

2

0

3

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0,33246

22

STANIULYTE Ruta
(VOLERO LE CANNET)

1

1

0

0

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0,33246

23

YOSIL SEVERINO Mesalina
(CHAMALIERES)

1

1

0

1

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0,33246

24

ANDRIAMAHERIZO - RANAIVO MARIE RAPHAELLE
(VOLERO LE CANNET)

1

3

0

1

0

8

0

0

0

0

0

0

0

0

1

1

1

4

-0,75

-0,75

0,33118

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