Teams

Clan Diamond Shark-E

2024 18&Over Mixed · 7.0

16 players · average NTRP 3.73 / NEW JERSEY REGION

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 →
Schedule9 played
2024-03-16vs What A RacquetWon 10
W#1 DoublesQiongrong Nie / Harish Kumar vs Sherla Glasgow / Hong Wang6-3, 6-2
2024-03-09vs Everlasting LobstoppersLost 01
L#1 DoublesArun Kanagasabapathy / Lynne Buchman vs Kathy Tsang / Richard Liu1-6, 2-6
2024-03-02vs No Strings AttachedWon 10
W#1 DoublesHarish Kumar / Qiongrong Nie vs Bruno Maguino / Alison North6-3, 2-6, 1-0
2024-02-24vs No Strings AttachedLost 01
L#1 DoublesHarish Kumar / Qiongrong Nie vs Olga Carey / Patryk Hirsz4-6, 4-6
2024-02-17vs Team WassermanWon 10
W#1 DoublesQiongrong Nie / Harish Kumar vs Richard Liu / Yijun Lu7-5, 6-0
2024-02-11vs Everlasting LobstoppersWon 20
W#1 DoublesChloris Li / Harish Kumar vs Nischint Manelkar / Arathi Reddy4-6, 6-5, 1-0
W#2 DoublesLynne Buchman / Tyler Harris vs Manan Jani / RANEE KUMAR6-0, 6-2
2024-02-02vs What A RacquetLost 01
L#3 DoublesRitch Belen / Roslyn Yang vs AUSTIN KIM / Soo Kim4-6, 4-6
2024-01-27vs No Strings AttachedSplit 11
W#2 DoublesArun Kanagasabapathy / Lynne Buchman vs Bruno Maguino / Li Liu7-5, 1-6, 1-0
L#3 DoublesPaul Fang / Ping Su vs Colton van Mol / Rachel Juliana3-6, 2-6
2024-01-12vs What A RacquetWon 10
W#3 DoublesRitch Belen / Roslyn Yang vs Alexander Ainge / Lynne Ainge4-6, 6-4, 1-0
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 standings2 teams · 7.0
TeamWLInd. WInd. LSets lostGames lost
1What A Racquet09161124226
2Clan Diamond Shark-E09151231231

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 3.54 estimated across 13 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.

4.01
Harish Kumar
usually #1 Doubles 83%, also #3 Doubles 17% · published
3.83
Roslyn Yang
usually #3 Doubles 58%, also #2 Doubles 25% · published 4
3.75
Madhu Talupur
usually #3 Doubles 50%, also #2 Doubles 33% · published
3.68
Lynne Buchman
usually #2 Doubles 67%, also #1 Doubles 33% · published 4
3.65
Ritch Belen
usually #3 Doubles 100% · published 4
3.61
Qiongrong Nie
usually #1 Doubles 55%, also #2 Doubles 27% · published 4
3.52
Liyun Feng
usually #2 Doubles 50%, also #1 Doubles 42% · published 3.5
3.48
Allison Bloch
usually #2 Doubles 43%, also #1 Doubles 43% · published 3.5
3.40
Paul Fang
usually #2 Doubles 54%, also #3 Doubles 27% · published 4
3.30
Tina Gonzalez
usually #3 Doubles 40%, also #2 Doubles 40% · published
3.28
Arun Kanagasabapathy
usually #2 Doubles 50%, also #1 Doubles 50% · published 3.5
Andrew Thurston
usually #3 Doubles 67%, also #2 Doubles 33% · published 3.5
3.24
Yunyun Xiong
usually #3 Doubles 50%, also #2 Doubles 38% · published 3.5
3.23
Chloris Li
usually #1 Doubles 43%, also #3 Doubles 29% · published 3.5
Ping Su
usually #3 Doubles 100% · published
Tyler Harris
usually #1 Doubles 56%, also #2 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.

Tina Gonzalez + Tyler Harris9260% games+18.1% vs expected
Harish Kumar + Qiongrong Nie5165% games+14.0% vs expected
Roslyn Yang + Paul Fang19563% games+13.7% vs expected
Tyler Harris + Allison Bloch5257% games−1.6% vs expected
Liyun Feng + Paul Fang4258% gamesnot enough data
Chloris Li + Paul Fang2443% gamesnot enough data
Roslyn Yang + Ritch Belen4153% gamesnot enough data
Tina Gonzalez + Paul Fang404 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.

Harish Kumar
126W–34L career · 6 lines in 2024
<1%46%54%
4.01
4
Roslyn Yang
123W–28L career · 12 lines in 2024
1%88%11%
3.83
Madhu Talupur
62W–37L career · 6 lines in 2024
4%93%4%
3.75
4
Lynne Buchman
212W–93L career · 3 lines in 2024
10%89%1%
3.68
4
Ritch Belen
123W–137L career · 2 lines in 2024
14%86%1%
3.65
4
Qiongrong Nie
90W–30L career · 11 lines in 2024
21%79%<1%
3.61
3.5
Liyun Feng
123W–49L career · 12 lines in 2024
<1%44%56%
3.52
3.5
Allison Bloch
281W–149L career · 7 lines in 2024
<1%54%46%
3.48
4
Paul Fang
217W–98L career · 26 lines in 2024
77%23%<1%
3.40
Tina Gonzalez
171W–134L career · 10 lines in 2024
2%91%8%
3.30
3.5
Arun Kanagasabapathy
57W–69L career · 2 lines in 2024
2%92%6%
3.28
3.5
Andrew Thurston
8W–3L career · 3 lines in 2024
not enough data
3.5
Yunyun Xiong
68W–70L career · 8 lines in 2024
4%93%3%
3.24
3.5
Chloris Li
115W–69L career · 7 lines in 2024
5%92%3%
3.23
Ping Su
3W–5L career · 1 line in 2024
not enough data
Tyler Harris
174W–54L career · 9 lines in 2024
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.