← All tennis
Set by set
| Player | Set 1 | Set 2 | Sets |
|---|---|---|---|
| M. Thompson | 1 | 1 | 0 |
| O. Dartawan | 6 | 6 | 2 |
Match facts
Tournament
UTR PTT Ithaca Women 01
Category
Utr
Surface
hard
Court
Reis Tennis Center (Cornell) - Court 5
City
Ithaca
First serve
M. Thompson
Total games
2–12
Recent form
M. Thompson
L N. Knezkova 0–2O. Dartawan
M. Thompson · match stats · O. Dartawan
1Aces1
1Double faults2
66%First serve in64%
46%First-serve points won71%
94%Second serve in88%
39%Second-serve points won69%
58%Break points saved100%
0%Break points converted42%
30%Return points won57%
23Service points won31
13Receiver points won30
36Total points won61
2Games won12
2Service games won7
0Tiebreaks won0
4Longest point streak8
1Longest game streak7
Per set · aces & double faults
| Set | Aces | Double faults |
|---|---|---|
| Set 1 | 1–0 | 1–2 |
| Set 2 | 0–1 | 0–0 |
Figures read M. Thompson first.
Set 230 min · 7 games · newest first
1-5
game 7
O. Dartawan serving
0-15
0-30
0-40
15-40
1-5
game 6
M. Thompson serving
15-0
30-0
40-0
40-15
0-5
game 5
O. Dartawan serving
0-15
0-30
0-40
0-4
game 4
M. Thompson serving
BREAK
15-0
15-15
15-30
15-40
30-40
0-3
game 3
O. Dartawan serving
0-15
0-30
15-30
15-40
0-2
game 2
M. Thompson serving
BREAK
0-15
0-30
0-40
0-1
game 1
O. Dartawan serving
15-0
15-15
15-30
15-40
30-40
40-40
40-A
Set 140 min · 7 games · newest first
1-6
game 7
M. Thompson serving
BREAK
15-0
15-15
15-30
15-40
30-40
40-40
40-A
40-40
A-40
40-40
40-A
40-40
40-A
40-40
40-A
40-40
40-A
1-5
game 6
O. Dartawan serving
0-15
0-30
15-30
15-40
30-40
1-4
game 5
M. Thompson serving
0-15
15-15
30-15
40-15
0-4
game 4
O. Dartawan serving
0-15
15-15
15-30
30-30
30-40
0-3
game 3
M. Thompson serving
BREAK
0-15
15-15
15-30
15-40
0-2
game 2
O. Dartawan serving
15-0
30-0
30-15
30-30
40-30
40-40
A-40
40-40
40-A
0-1
game 1
M. Thompson serving
BREAK
0-15
15-15
30-15
40-15
40-30
40-40
A-40
40-40
40-A
Point chips read M. Thompson first · highlighted border marks the point winner.
Win probability
M. ThompsonO. Dartawan
50%
Model confidence
Why the model thinks so
- Very evenly matched
How the model did
Predicted M. Thompson
— wrong