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W15 Sharm Elsheikh



W15 Sharm Elsheikh Women ITF Women - Singles - Egypt 2023

ITF Women - Singles W15 Sharm Elsheikh is a tennis tournament played in Egypt. There are 44 players competing in the 2023 Women season. Among the players competing in the W15 Sharm Elsheikh are Nina Rudiukova, Denise Hrdinkova, Georgia Pedone, E. Krokhina. Browse below for the W15 Sharm Elsheikh 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

Round 1

Trends

E. Visnevscaia has won 100.00% of sets played in all W15 Sharm Elsheikh matches
Ching Wu Ho has won 86.67% of sets played in all W15 Sharm Elsheikh matches
Ching Wu Ho has won all 1st sets in the last 7 matches played at W15 Sharm Elsheikh
Linda Klimovicova has won 80.00% of sets played in all W15 Sharm Elsheikh matches
Darja Suvirdjonkova has won 80.00% of sets played in all W15 Sharm Elsheikh matches
Alexia Todoni Anca has won all 1st sets in the last 3 matches played at W15 Sharm Elsheikh

Players – Set Performance

Player NamePerformanceMatchesAverage
Ching Wu Ho 117 2.14
Darya Shauha 76 2.50
Eszter Meri 46 2.00
Katarina Kuzmova 44 2.00
Klaudija Bubelyte 44 2.00
Alexia Todoni Anca 33 2.33
Darja Suvirdjonkova 32 2.50
Georgia Pedone 34 2.25
Linda Klimovicova 32 2.50
E. Visnevscaia 21 2.00
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
A. Maheshkumar 16.00 0.00 %
Alexia Todoni Anca 19.33 33.33 %
Amelia Waligora 17.50 0.00 %
Anastasiya Apalikhina 20.50 50.00 %
Andreea Herea Carmen 14.00 0.00 %
B. Michalkova 26.00 100.00 %
Cheong-Eui Kim 19.00 50.00 %
Chiara Girelli 13.50 0.00 %
Ching Wu Ho 17.57 14.29 %
Darja Suvirdjonkova 22.50 50.00 %
Darya Shauha 22.67 50.00 %
Denise Hrdinkova 20.50 0.00 %
E. Krokhina 14.00 0.00 %
E. Tverijonaite 19.00 33.33 %
E. Visnevscaia 21.00 50.00 %
Eszter Meri 16.67 0.00 %
Evgeniya Burdina 20.00 50.00 %
Georgia Pedone 19.25 25.00 %
Giuliana Bestetti 18.50 0.00 %
Honoka Kobayashi 17.67 0.00 %
I. Iudenko 26.00 100.00 %
Ivana Sebestova 21.67 33.33 %
K. Pavlova 22.50 50.00 %
Katarina Kuzmova 18.75 0.00 %
Kim Eunchae 19.00 0.00 %
Klaudija Bubelyte 19.50 0.00 %
L. Rasskovskaia 21.00 0.00 %
Lara Pfeifer 17.00 0.00 %
Linda Klimovicova 19.00 0.00 %
Maggie Ng Man Ying 18.00 0.00 %
Merna Refaat 16.50 0.00 %
Michika Ozeki 24.20 60.00 %
N. Benesova 15.00 0.00 %
Nina Rudiukova 20.00 0.00 %
Radka Zelnickova 21.25 50.00 %
S. Bojica 16.00 0.00 %
S. Milanese 20.67 33.33 %
Sabina Dadaciu 22.00 0.00 %
Salma Drugdova 16.50 0.00 %
Sara Popa Maria 18.00 0.00 %
Selina Dal 23.00 50.00 %
Virginia Ferrara 32.00 100.00 %
Yujiao Che 14.00 0.00 %
Ziva Falkner 15.33 0.00 %
Tournament Avg.   22.33%
Data in above table is calculated from finished matches only.

Clean Sheets

Player Name CS Pld Perc.
Ching Wu Ho 6 7 85.71%
Eszter Meri 4 6 66.67%
Darya Shauha 3 6 50.00%
Katarina Kuzmova 3 4 75.00%
Klaudija Bubelyte 3 4 75.00%
Alexia Todoni Anca 2 3 66.67%
Amelia Waligora 2 4 50.00%
Georgia Pedone 2 4 50.00%
Radka Zelnickova 2 4 50.00%
Salma Drugdova 2 4 50.00%
Darja Suvirdjonkova 1 2 50.00%
E. Tverijonaite 1 3 33.33%
E. Visnevscaia 1 1 100.00%
Honoka Kobayashi 1 3 33.33%
Ivana Sebestova 1 3 33.33%
K. Pavlova 1 4 25.00%
Linda Klimovicova 1 2 50.00%
Merna Refaat 1 2 50.00%
Michika Ozeki 1 5 20.00%
S. Milanese 1 3 33.33%
Selina Dal 1 4 25.00%
Ziva Falkner 1 3 33.33%
A. Maheshkumar 0 1 0.00%
Anastasiya Apalikhina 0 1 0.00%
Andreea Herea Carmen 0 1 0.00%
B. Michalkova 0 1 0.00%
Cheong-Eui Kim 0 1 0.00%
Chiara Girelli 0 2 0.00%
Denise Hrdinkova 0 2 0.00%
E. Krokhina 0 1 0.00%
Evgeniya Burdina 0 2 0.00%
Giuliana Bestetti 0 1 0.00%
I. Iudenko 0 1 0.00%
Kim Eunchae 0 1 0.00%
L. Rasskovskaia 0 1 0.00%
Lara Pfeifer 0 1 0.00%
Maggie Ng Man Ying 0 1 0.00%
N. Benesova 0 1 0.00%
Nina Rudiukova 0 1 0.00%
S. Bojica 0 1 0.00%
Sabina Dadaciu 0 1 0.00%
Sara Popa Maria 0 1 0.00%
Virginia Ferrara 0 1 0.00%
Yujiao Che 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%
A. Maheshkumar0 0.00%
Alexia Todoni Anca3 71.43%
Amelia Waligora0 50.00%
Anastasiya Apalikhina1 20.00%
Andreea Herea Carmen0 0.00%
B. Michalkova1 33.33%
Cheong-Eui Kim0 40.00%
Chiara Girelli0 0.00%
Ching Wu Ho7 86.67%
Darja Suvirdjonkova2 80.00%
Darya Shauha1 73.33%
Denise Hrdinkova0 0.00%
E. Krokhina0 0.00%
E. Tverijonaite0 57.14%
E. Visnevscaia2 100.00%
Eszter Meri0 66.67%
Evgeniya Burdina0 40.00%
Georgia Pedone2 66.67%
Giuliana Bestetti0 0.00%
Honoka Kobayashi0 42.86%
I. Iudenko0 33.33%
Ivana Sebestova0 42.86%
K. Pavlova0 50.00%
Katarina Kuzmova2 75.00%
Kim Eunchae0 0.00%
Klaudija Bubelyte1 75.00%
L. Rasskovskaia0 0.00%
Lara Pfeifer0 0.00%
Linda Klimovicova2 80.00%
Maggie Ng Man Ying0 0.00%
Merna Refaat0 50.00%
Michika Ozeki0 53.85%
N. Benesova0 0.00%
Nina Rudiukova0 0.00%
Radka Zelnickova0 55.56%
S. Bojica0 0.00%
S. Milanese0 42.86%
Sabina Dadaciu0 0.00%
Salma Drugdova0 50.00%
Sara Popa Maria0 0.00%
Selina Dal2 60.00%
Virginia Ferrara0 33.33%
Yujiao Che0 0.00%
Ziva Falkner0 33.33%
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 W15 Sharm Elsheikh 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 ITF Women - Singles W15 Sharm Elsheikh. 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