Teams

CUESTA TC 18MX10.0A

2026 MIXED 18&Over · 18&Over MX10.0

19 players · average NTRP 4.89 / 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 →
Schedule7 played
2026-03-14vs BAY CLUB COURTSIDE 18MX10.0ALost 01
L#3 DoublesCatherine Clements / Matt Romano vs Joel Hunter / Lauren Stuckey0-6, 0-6
2026-02-28vs SUNNYVALE MTC 18MX10.0BSplit 11
L#2 DoublesNishanth Dikkala / Winnie Zhang vs Christi Tain / Jason Ah Chuen Jahchuen3-6, 3-6
W#3 DoublesJuan Castillo / Catherine Clements vs Xiaoyu Ma / Alexander Liu6-2, 3-6, 1-0
2026-02-21vs BAY CLUB COURTSIDE 18MX10.0ALost 01
L#2 DoublesNishanth Dikkala / Catherine Clements vs Shiraz Madan / Valerie Thong1-6, 3-6
2026-01-30vs SUNNYVALE MTC 18MX10.0BLost 01
L#3 DoublesAnusha Arcalgud / Austin Peng vs Jason Ah Chuen Jahchuen / Ashley Yeah3-6, 3-6
2026-01-19vs SUNNYVALE MTC 18MX10.0BLost 01
L#2 DoublesYui Tantiyavarong / Steven Chung vs Ashley Yeah / Allen Shih1-6, 1-6
2026-01-17Lost 01
L#1 DoublesNishanth Dikkala / Yui Tantiyavarong vs Darrin Cohen / Emily Zhang0-6, 1-6
2026-01-10vs BAY CLUB COURTSIDE 18MX10.0ALost 01
L#3 DoublesJulia Ling / Austin Peng vs Danielle Caro / Joseph Teh0-6, 2-6
A tie can be incomplete. Tell us if someone is missing.
i
Grouped by tie — one fixture, several lines. A line shows only when a player on it is someone we have indexed, so an early-season tie for a newly-added team can look short. This also means the line count here will not match the header, which counts individual player appearances.
Flight standings7 teams · 18&Over MX10.0
TeamWLInd. WInd. LSets lostGames lost
1SUNNYVALE MTC 18MX10.0B9125514180
2GOLDMAN TC 18MX10.0A7322819211
3CALIFORNIA TC 18MX10.0A73201023223
4OLYMPIC 18MX10.0A64151535288
5BAY CLUB COURTSIDE 18MX10.0A55161431248
6CUESTA TC 18MX10.0A1942655353
7MILLS COLLEGE 18MX10.0A01032757354

Ordered by team wins, then losses, then sets lost — the order USTA uses to seed a flight. Individual wins are lines, not ties.

See the full flight, with every team’s record

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 4.31 estimated across 16 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.

Ankita Saavedra
usually #1 Doubles 100% · published 5.5
4.84
Atsuko Saito
usually #3 Doubles 57%, also #2 Doubles 29% · published 5
Austin Peng
usually #3 Doubles 100% · published 5
4.53
Amogh Mellacheruvu
usually #1 Doubles 80%, also #3 Doubles 20% · published 5
4.52
Katerina Ng
usually #1 Doubles 100% · published
4.47
Maiko Yano
usually #1 Doubles 36%, also #2 Doubles 36% · published
4.46
William Trevillyan
usually #1 Doubles 40%, also #3 Doubles 40% · published
4.43
Catherine Clements
usually #3 Doubles 67%, also #2 Doubles 33% · published 5
4.41
Julia Ling
usually #3 Doubles 83%, also #2 Doubles 17% · published
4.37
Steven Chung
usually #2 Doubles 100% · published
4.33
Denis Sergeychik
usually #2 Doubles 71%, also #1 Doubles 29% · published 5
4.24
Deepak Srikanth
usually #1 Doubles 50%, also #2 Doubles 50% · published 4.5
4.19
Dan Nandra
usually #1 Doubles 50%, also #3 Doubles 50% · published 4.5
4.17
Matt Romano
usually #3 Doubles 40%, also #1 Doubles 40% · published
4.13
Anusha Arcalgud
usually #1 Doubles 44%, also #3 Doubles 33% · published 4.5
4.12
Winnie Zhang
usually #2 Doubles 46%, also #3 Doubles 27% · published
3.99
Surik Torosyan
usually #1 Doubles 67%, also #3 Doubles 33% · published
3.81
Yui Tantiyavarong
usually #2 Doubles 56%, also #3 Doubles 33% · published
Nishanth Dikkala
usually #2 Doubles 67%, also #1 Doubles 33% · published
Established pairs

Doubles pairs from this roster with three or more matches together anywhere — ordered by performance against what the rating gap predicted, not by record.

Yui Tantiyavarong + Denis Sergeychik033 matchesnot enough data
Deepak Srikanth + Maiko Yano123 matchesnot enough data
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.

5.5
Ankita Saavedra
0W–1L career · 1 line in 2026
not enough data
5
Atsuko Saito
15W–6L career · 7 lines in 2026
no projection at this level
4.84
5
Austin Peng
0W–2L career · type S · 2 lines in 2026
not enough data
5
Amogh Mellacheruvu
1W–12L career · 5 lines in 2026
no projection at this level
4.53
Katerina Ng
2W–4L career · 2 lines in 2026
no projection at this level
4.52
Maiko Yano
11W–6L career · 11 lines in 2026
<1%57%43%
4.47
William Trevillyan
6W–7L career · 5 lines in 2026
no projection at this level
4.46
5
Catherine Clements
3W–7L career · 3 lines in 2026
no projection at this level
4.43
Julia Ling
3W–8L career · 6 lines in 2026
no projection at this level
4.41
Steven Chung
1W–7L career · 1 line in 2026
no projection at this level
4.37
5
Denis Sergeychik
6W–13L career · 7 lines in 2026
no projection at this level
4.33
4.5
Deepak Srikanth
2W–3L career · 4 lines in 2026
5%92%3%
4.24
4.5
Dan Nandra
5W–8L career · 4 lines in 2026
8%90%1%
4.19
Matt Romano
9W–11L career · 5 lines in 2026
11%88%1%
4.17
4.5
Anusha Arcalgud
9W–15L career · 9 lines in 2026
17%83%<1%
4.13
Winnie Zhang
13W–25L career · 11 lines in 2026
19%81%<1%
4.12
Surik Torosyan
1W–9L career · 3 lines in 2026
no projection at this level
3.99
Yui Tantiyavarong
6W–28L career · 9 lines in 2026
92%8%<1%
3.81
Nishanth Dikkala
0W–3L career · 3 lines in 2026
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.