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Madrid Women Double WTA - Doubles - Spain 2023

WTA - Doubles Madrid is a tennis tournament played in Spain. There are 64 players competing in the 2023 Women Double season. Among the players competing in the Madrid are Kenin/ Linette, Krawczyk/ Schuurs, Kichenok/ Ostapenko, Kalinskaya/ McNally. Browse below for the Madrid match results and fixtures, tennis trends or over/under number of games among other various statistics like 1st Set win sequence or set winning averages.

Final

Semi Finals

Quarter Finals

Round 3

Round 2

29/04/2023 Fernandez/ Townsend
2 - 0
Kichenok/ Ostapenko
29/04/2023 Olmos/ Panova
2 - 0
Flipkens/ Rosolska
29/04/2023 Hunter/ Mertens
2 - 0
Kasatkina/ Trevisan
29/04/2023 Mihalikova/ Parks
0 - 2
Kalashnikova/ Sizikova
29/04/2023 Siegemund/ Zvonareva
1 - 2
Kalinskaya/ McNally
29/04/2023 Hsieh S-/Strycova
2 - 1
Aryna Sabalenka
29/04/2023 Melichar-Martinez/ Perez
0 - 1
Kato/ Sutjiadi
28/04/2023 Babos/ Danilina
1 - 2
Kostyuk/ Ruse
28/04/2023 Kichenok/ Zimmermann
1 - 2
Andreeva/ Andreeva
28/04/2023 Kudermetova/ Samsonova
1 - 2
Niculescu/ Ninomiya
28/04/2023 Badosa/ Mattek-Sands
2 - 1
Fruhvirtova/ Fruhvirtova
28/04/2023 Kenin/ Linette
1 - 2
Dabrowski/ Stefani
27/04/2023 Gauff/ Pegula
2 - 0
Guarachi/ Routliffe
27/04/2023 Azarenka/ Haddad Maia
2 - 1
Krawczyk/ Schuurs
27/04/2023 Pavlyuchenkova/ Rybakina
2 - 0
Aoyama/ Shibahara
27/04/2023 Xu/ Yang
2 - 0
Alexandrova/ Potapova

Round 1

Trends

Pavlyuchenkova/ Rybakina has won 100.00% of sets played in all Madrid matches
Azarenka/ Haddad Maia has won 80.00% of sets played in all Madrid matches
Azarenka/ Haddad Maia has won all 1st sets in the last 4 matches played at Madrid

Players – Set Performance

Player NamePerformanceMatchesAverage
Azarenka/ Haddad Maia 64 2.50
Fernandez/ Townsend 54 2.25
Gauff/ Pegula 55 2.20
Dabrowski/ Stefani 23 2.67
Pavlyuchenkova/ Rybakina 21 2.00
Badosa/ Mattek-Sands 13 2.33
Hsieh S-/Strycova 13 2.33
Hunter/ Mertens 12 2.50
Kalinskaya/ McNally 11 3.00
Niculescu/ Ninomiya 13 3.00
Data in above table is calculated for Set Performance as number of sets won minus number of sets lost along the tournament.

Over/Under

Matches of... Total games score (player + opponent)
Avg. over 22.5
Alexandrova/ Potapova 20.00 0.00 %
Andreeva/ Andreeva 29.00 50.00 %
Aoyama/ Shibahara 13.00 0.00 %
Aryna Sabalenka 28.00 100.00 %
Azarenka/ Haddad Maia 27.00 75.00 %
Babos/ Danilina 42.00 100.00 %
Badosa/ Mattek-Sands 26.33 66.67 %
Dabrowski/ Stefani 30.00 66.67 %
Fernandez/ Townsend 22.50 25.00 %
Flipkens/ Rosolska 19.00 0.00 %
Fruhvirtova/ Fruhvirtova 38.00 100.00 %
Gauff/ Pegula 24.80 60.00 %
Guarachi/ Routliffe 26.00 100.00 %
Hsieh S-/Strycova 21.67 33.33 %
Hunter/ Mertens 27.00 50.00 %
Kalashnikova/ Sizikova 21.00 0.00 %
Kalinskaya/ McNally 38.00 100.00 %
Kasatkina/ Trevisan 18.00 0.00 %
Kato/ Sutjiadi 15.50 0.00 %
Kenin/ Linette 35.00 100.00 %
Kichenok/ Ostapenko 18.00 0.00 %
Kichenok/ Zimmermann 37.00 100.00 %
Kostyuk/ Ruse 32.67 100.00 %
Krawczyk/ Schuurs 34.00 100.00 %
Kudermetova/ Samsonova 35.00 100.00 %
Melichar-Martinez/ Perez 13.00 0.00 %
Mihalikova/ Parks 21.00 0.00 %
Niculescu/ Ninomiya 34.00 100.00 %
Olmos/ Panova 20.50 0.00 %
Pavlyuchenkova/ Rybakina 13.00 0.00 %
Siegemund/ Zvonareva 38.00 100.00 %
Xu/ Yang 18.00 0.00 %
Tournament Avg.   50.83%
Data in above table is calculated from finished matches only.

Clean Sheets

Player Name CS Pld Perc.
Fernandez/ Townsend 3 4 75.00%
Gauff/ Pegula 3 5 60.00%
Azarenka/ Haddad Maia 2 4 50.00%
Badosa/ Mattek-Sands 1 3 33.33%
Dabrowski/ Stefani 1 3 33.33%
Hsieh S-/Strycova 1 3 33.33%
Hunter/ Mertens 1 2 50.00%
Kalashnikova/ Sizikova 1 2 50.00%
Kato/ Sutjiadi 1 2 50.00%
Olmos/ Panova 1 2 50.00%
Pavlyuchenkova/ Rybakina 1 1 100.00%
Xu/ Yang 1 2 50.00%
Alexandrova/ Potapova 0 1 0.00%
Andreeva/ Andreeva 0 1 0.00%
Aoyama/ Shibahara 0 1 0.00%
Aryna Sabalenka 0 1 0.00%
Babos/ Danilina 0 1 0.00%
Flipkens/ Rosolska 0 1 0.00%
Fruhvirtova/ Fruhvirtova 0 1 0.00%
Guarachi/ Routliffe 0 1 0.00%
Kalinskaya/ McNally 0 1 0.00%
Kasatkina/ Trevisan 0 1 0.00%
Kenin/ Linette 0 1 0.00%
Kichenok/ Ostapenko 0 1 0.00%
Kichenok/ Zimmermann 0 1 0.00%
Kostyuk/ Ruse 0 3 0.00%
Krawczyk/ Schuurs 0 1 0.00%
Kudermetova/ Samsonova 0 1 0.00%
Melichar-Martinez/ Perez 0 1 0.00%
Mihalikova/ Parks 0 1 0.00%
Niculescu/ Ninomiya 0 3 0.00%
Siegemund/ Zvonareva 0 1 0.00%
Data in above table lists the number of clean sheets (matches with no lost sets) out of total matches played by each player in this tournament. All finished and retired matches are counted towards these statistics.

Form – Win Sequences

Player NameWin 1st SetSet Win%
Alexandrova/ Potapova0 0.00%
Andreeva/ Andreeva0 40.00%
Aoyama/ Shibahara0 0.00%
Aryna Sabalenka1 33.33%
Azarenka/ Haddad Maia4 80.00%
Babos/ Danilina0 33.33%
Badosa/ Mattek-Sands0 57.14%
Dabrowski/ Stefani0 62.50%
Fernandez/ Townsend0 77.78%
Flipkens/ Rosolska0 0.00%
Fruhvirtova/ Fruhvirtova1 33.33%
Gauff/ Pegula0 72.73%
Guarachi/ Routliffe0 0.00%
Hsieh S-/Strycova0 57.14%
Hunter/ Mertens0 60.00%
Kalashnikova/ Sizikova0 50.00%
Kalinskaya/ McNally0 66.67%
Kasatkina/ Trevisan0 0.00%
Kato/ Sutjiadi0 33.33%
Kenin/ Linette1 33.33%
Kichenok/ Ostapenko0 0.00%
Kichenok/ Zimmermann1 33.33%
Kostyuk/ Ruse0 50.00%
Krawczyk/ Schuurs0 33.33%
Kudermetova/ Samsonova1 33.33%
Melichar-Martinez/ Perez0 0.00%
Mihalikova/ Parks0 0.00%
Niculescu/ Ninomiya2 55.56%
Olmos/ Panova0 50.00%
Pavlyuchenkova/ Rybakina1 100.00%
Siegemund/ Zvonareva1 33.33%
Xu/ Yang0 50.00%
Data in above table lists consecutive 1st Set wins by each player. When 1st Set is lost, data is reset. Set Win percentage shows the winning percentage out of total sets played by each player in this tournament. All finished and retired matches are counted towards these statistics.

The statistics for the tennis tournament Madrid are updated regularly, as games are played and results are processed. Data shown in these statistics is organized to make it easy to identify tournament trends and probabilities for future tennis games, something that TennisStats247 system uses to calculate the predictions for WTA - Doubles Madrid. The Predictions section comes with updated daily tips as our algorithm calculates probabilities for various outcomes in tennis games and it improves as more tennis statistics are available from matches played.

Seasons