Teams

GLTF/GOLDMAN TC 18MX7.0B

2022 MIXED 18&Over · 18&Over MX7.0

20 players · average NTRP 3.50 / NO. CALIFORNIA

No matches recorded for this roster in this league — it may be a placeholder registration, or the season may not have started.

View scouting list →

Flight standings for 18&Over MX7.0 have not been collected yet. Where we have them we show every team in the flight ranked, with this team highlighted. The crawler is still filling in older seasons and flights.

ScoutingWhere each opponent usually plays

Signed-in extra: whether this captain plays strict strength order or mixes it up, from every doubles line they have put out. Create a free account to see it.

Roster averages 3.21 estimated across 19 rated players. No lineup is published in advance, so the column below is where each player has actually been used — a captain's habits are the best available forecast. Sign in and claim your record to see who you have played.

3.64
3.56
Joni Fuse
published
3.38
Grace Chan
published 3.5
3.35
Daniel Lim
published 3.5
3.32
Patty Nunez
published
3.30
Alvin Cheng
published 3.5
3.30
Mei M Wong
published
3.27
Anuj Agarwal
published 3.5
3.26
Sean Avent
published
3.22
Tiffany Truong
published
3.19
Guru Prasad Acharya
published 3.5
3.17
Daniel Bao
published 3.5
3.16
Jong-Chyi Su
published
3.15
Tom Januario
published
3.10
Timothy Tuttle
published
3.00
Ivan Iannoli
published 3.5
2.95
Robb Young
published
2.92
K Janelle Lee
published
2.68
William Char
published
Katrina Salsburey
published
Roster

Ordered by our estimated dynamic rating, which is why two players at the same published level are not tied — a published 4.0 says nothing about where inside the band someone sits. Lines played in this team’s season are shown beside each name.

3.5
Christopher Stephenson
10W–1L career · no lines in 2022
<1%13%87%
3.64
Joni Fuse
12W–8L career · no lines in 2022
33%67%<1%
3.56
3.5
Grace Chan
13W–5L career · no lines in 2022
<1%82%18%
3.38
3.5
Daniel Lim
33W–31L career · no lines in 2022
<1%88%12%
3.35
Patty Nunez
9W–10L career · no lines in 2022
1%91%8%
3.32
3.5
Alvin Cheng
2W–8L career · no lines in 2022
1%93%6%
3.30
Mei M Wong
10W–3L career · no lines in 2022
1%93%6%
3.30
3.5
Anuj Agarwal
2W–1L career · type S · no lines in 2022
2%94%4%
3.27
Sean Avent
5W–11L career · no lines in 2022
2%94%3%
3.26
Tiffany Truong
5W–26L career · no lines in 2022
4%94%2%
3.22
3.5
Guru Prasad Acharya
11W–10L career · no lines in 2022
7%92%1%
3.19
3.5
Daniel Bao
7W–12L career · no lines in 2022
10%90%1%
3.17
Jong-Chyi Su
10W–1L career · no lines in 2022
11%88%<1%
3.16
Tom Januario
11W–10L career · no lines in 2022
13%87%<1%
3.15
Timothy Tuttle
7W–12L career · no lines in 2022
23%77%<1%
3.10
3.5
Ivan Iannoli
5W–6L career · no lines in 2022
50%50%<1%
3.00
Robb Young
8W–11L career · no lines in 2022
<1%66%34%
2.95
K Janelle Lee
5W–9L career · no lines in 2022
<1%73%27%
2.92
William Char
6W–10L career · no lines in 2022
8%91%1%
2.68
Katrina Salsburey
1W–1L career · no lines in 2022
not enough data

Three percentages are where each player stands right now: the chance they are below their band, inside it, or above it, on the way they are playing this season. The number on the right is our estimated dynamic rating, which USTA never publishes. This is today rather than a forecast of December, because a forecast has to assume future matches and cannot know whether someone will even be offered them. Percentages are blank where a player has too few matches this season, or at a level where the model does not yet beat a base-rate guess; the estimate is a weaker claim than a probability and survives where those do not.

Not affiliated with or endorsed by the USTA. Ratings labelled as published are USTA year-end figures; anything we describe as an estimate is ours, not USTA’s. Match data is from USTA TennisLink.