Savannah Broadus vs Abigail Haile — score & stats

Set by set

Player	Set 1	Set 2	Sets
S. Broadus	6	6	2
A. Haile	0	2	0

Momentum — game by game, ● = break

▲ S. Broadus ▼ A. Haile

Match facts

Tournament

UTR Newport Beach W02

S. Broadus

W S. Lau 2–0 W J. H. Gomez 2–0 W E. Jantacova 2–0 W K. Keller 2–0

A. Haile

W M. Magrini 2–0 W A. Duong 2–0 W M. Deng 2–0 W R. Levine 2–0 L M. Clark 1–2

S. Broadus · match stats · A. Haile

1Aces0

3Double faults3

52%First serve in68%

71%First-serve points won38%

86%Second serve in80%

45%Second-serve points won40%

75%Break points saved33%

67%Break points converted25%

62%Return points won41%

27Service points won18

29Receiver points won19

56Total points won37

12Games won2

6Service games won1

0Tiebreaks won0

6Longest point streak7

8Longest game streak2

Per set · aces & double faults

Set	Aces	Double faults
Set 1	0–0	1–0
Set 2	1–0	2–3

Figures read S. Broadus first.

Set 28 games · newest first

6-2 game 8 S. Broadus serving

15-0 15-15 15-30 30-30 40-30

5-2 game 7 A. Haile serving BREAK

15-0 30-0 40-0 40-15 40-30

4-2 game 6 S. Broadus serving

15-0 30-0 40-0 40-15 40-30

3-2 game 5 A. Haile serving BREAK

0-15 15-15 15-30 30-30 40-30

2-2 game 4 S. Broadus serving BREAK

0-15 0-30 0-40

2-1 game 3 A. Haile serving

0-15 0-30 15-30 30-30 30-40

2-0 game 2 S. Broadus serving

0-15 0-30 15-30 15-40 30-40 40-40 A-40

1-0 game 1 A. Haile serving BREAK

0-15 15-15 30-15 30-30 30-40 40-40 40-A 40-40 40-A 40-40 A-40

Set 16 games · newest first

6-0 game 6 S. Broadus serving

15-0 15-15 30-15 30-30 40-30

5-0 game 5 A. Haile serving BREAK

0-15 15-15 30-15 30-30 40-30

4-0 game 4 S. Broadus serving

0-15 15-15 15-30 30-30 40-30 40-40 A-40

3-0 game 3 A. Haile serving BREAK

15-0 15-15 30-15 30-30 40-30

2-0 game 2 S. Broadus serving

0-15 15-15 15-30 30-30 30-40 40-40 A-40

1-0 game 1 A. Haile serving BREAK

15-0 30-0 40-0 40-15

Point chips read S. Broadus first · highlighted border marks the point winner.

Win probability

S. BroadusA. Haile

54%

46%

54%

Model confidence

Why the model thinks so

Very evenly matched