Tennis · W15 Luan · 16/07, 04:00

Prediction: Naho Sato vs Gio Jang

Prediction summary
Winner
73% 27%
Naho Sato Gio Jang
Estimated games
19.1
Recent form · 10 last
Naho Sato 7-3 (W-L)
LLWWWLWWWW
Gio Jang 3-7 (W-L)
LLLLLWLWLW
Our model (Elo) vs Market Rating Elo · Naho Sato 1542 · Gio Jang 1510
Naho SatoGio Jang
Our model55%45%
Market88%12%

The bar above blends our model with the market: where our probability diverges most from the odds is where the model sees the widest gap.

Statistics

Naho SatoGio Jang
Win %60%50%
Win % · Hard 60% (10) 50% (10)
Sets (G-P)1.3-0.81-1.2
Games (G-P)10.2-7.37.6-9.2
Aces00.3
Double faults1.31.9
1st serve %59%55.8%
Break %57.8%42.2%
Estimated total games (ours) 19.1

Last 10 matches played

Last matches of each player (sets and games). W = win, L = loss. Common opponents to both are in blue.

Naho Sato

LWWLW

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Date Opponent Sets Games Res.
15/07 Junlu Sun
W15 Luan · ~Hard
2-0 12-1 W
25/06 Gyeong Seo Lee
W35 Taipei · ~Hard
1-2 12-17 L
23/06 Eunhye Lee
W35 Taipei · ~Hard
2-0 12-2 W
22/06 Nao Phang Ziyi
W35 Taipei · ~Hard
2-0 12-0 W
19/06 Dayeon Back
W35 Taipei · ~Hard
0-2 7-13 L
18/06 Sakura Hosogi
W35 Taipei · ~Hard
2-0 12-8 W
17/06 Feier Hu
W35 Taipei · ~Hard
2-0 12-6 W
15/06 Ji Min Park
W35 Taipei · ~Hard
2-0 12-1 W
09/06 Kayo Nishimura
W15 Tokyo · ~Hard
0-2 4-12 L
22/05 Jia-Jing Lu
W35 Changwon · ~Hard
0-2 7-13 L

Gio Jang

WWWLW

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Date Opponent Sets Games Res.
15/07 Sa Rang Lim
W15 Luan · ~Hard
2-0 7-2 W
22/05 Dabin Kim
W35 Changwon · ~Hard
1-2 13-13 L
22/05 Anchisa Chanta
W35 Changwon · ~Hard
2-0 8-4 W
21/05 Amy Zhu
W35 Changwon · ~Hard
2-1 13-11 W
19/05 Hee Rae Im
W35 Changwon · ~Hard
1-0 6-4 W
13/05 JiaYi Wang
W15 Luan · ~Hard
0-2 4-12 L
12/05 Peien Deng
W15 Luan · ~Hard
2-1 13-10 W
05/05 Ye Eun Kim
W15 Luan · ~Hard
0-2 6-12 L
27/04 Onyu Choi
W35 Goyang · ~Hard
0-2 1-12 L
18/11 Sofiia Nagornaia
ITF W15 Hua Hin · Hard
0-2 5-12 L

Frequently asked questions

Who is the favourite in Naho Sato vs Gio Jang?

Our model gives 73% to Naho Sato, using surface Elo on hard.

What is the prediction based on?

On an Elo model by surface (hard) adjusted for opponent quality, compared with the market odds.