Teams

WTF?! (what the forehand)

2022 Mixed 18 and Over League · 8.0

15 players · average NTRP 4.06 / EAST HAWAII

View scouting list →
Schedule6 played
2022-05-01vs Lone ServivorsWon 30
W#1 DoublesLiane Martin / Ryan Liu vs Adamhung Nguyen / Lori Kamimura6-4, 7-5
W#2 DoublesMark Chun / Marissa Hayashi vs Lance Sewake / Tomomi Furuhata2-1
W#3 DoublesTomoyuki Furuhata / Reiko Hamano vs Duane Sleightholm / Marianne Takamiya1-0
2022-05-01vs Lone ServivorsWon 21
W#1 DoublesChristopher Agpoon / Michelle Oishi vs Peter Follett / Reiko Bando6-4, 6-1
W#2 DoublesNikki Ideta / Kuakini Baltero vs Lori Nekoba / Kareem Khozaim4-6, 6-4, 1-0
L#3 DoublesGrant Yamamoto / Liane Martin vs Lance Sewake / Tomomi Furuhata3-6, 6-3, 0-1
2022-04-21vs Lone ServivorsWon 30
W#1 DoublesKari Wicklund / Mark Chun vs TAKAMASA BANDO / Hanna Wilson6-1, 6-7, 1-0
W#2 DoublesTomoyuki Furuhata / Reiko Hamano vs Adamhung Nguyen / Reiko Bando2-0
W#3 DoublesNicholas Tran / Sheri Kinoshita vs Peter Follett / Lori Kamimura6-2, 6-4
2022-04-21vs Lone ServivorsWon 21
W#1 DoublesChristopher Agpoon / Nikki Ideta vs Kareem Khozaim / Lori Nekoba6-4, 6-3
W#2 DoublesMarissa Hayashi / Haddon Wong Yuen vs Duane Sleightholm / Marianne Takamiya6-4, 1-6, 1-0
L#3 DoublesMichelle Oishi / Kuakini Baltero vs TAKAMASA BANDO / Hanna Wilson3-6, 4-6
2022-03-27vs Lone ServivorsWon 21
W#1 DoublesGrant Yamamoto / Liane Martin vs Duane Sleightholm / Hanna Wilson4-6, 6-2, 1-0
W#2 DoublesKari Wicklund / Haddon Wong Yuen vs Peter Follett / Lori Nekoba4-6, 6-1, 1-0
L#3 DoublesNicholas Tran / Michelle Oishi vs Kareem Khozaim / Lori Kamimura3-6, 2-6
2022-03-26vs Lone ServivorsWon 21
W#1 DoublesNikki Ideta / Ryan Liu vs TAKAMASA BANDO / Marianne Takamiya6-3, 4-6, 1-0
W#2 DoublesTomoyuki Furuhata / Reiko Hamano vs Reiko Bando / Adamhung Nguyen6-1, 6-4
L#3 DoublesKuakini Baltero / Sheri Kinoshita vs Lance Sewake / Tomomi Furuhata4-6, 3-6
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 standings2 teams · 8.0
TeamWLInd. WInd. LSets lostGames lost
1WTF?! (what the forehand)6014414131
2Lone Servivors0641429190

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 3.76 estimated across 10 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.

4.30
Tomoyuki Furuhata
usually #2 Doubles 67%, also #3 Doubles 33% · published 4.5
4.03
Kari Wicklund
usually #2 Doubles 50%, also #1 Doubles 50% · published 4
3.94
Marissa Hayashi
usually #2 Doubles 100% · published 4
3.84
Ryan Liu
usually #1 Doubles 100% · published
3.79
Sheri Kinoshita
usually #3 Doubles 100% · published 4
3.77
Nikki Ideta
usually #1 Doubles 67%, also #2 Doubles 33% · published 4
Christopher Agpoon
usually #1 Doubles 75%, also #3 Doubles 25% · published 4
3.57
Liane Martin
usually #1 Doubles 75%, also #3 Doubles 25% · published 4
3.56
Grant Yamamoto
usually #1 Doubles 50%, also #3 Doubles 50% · published 4
3.50
Michelle Oishi
usually #3 Doubles 67%, also #1 Doubles 33% · published 4
3.29
Mark Chun
usually #1 Doubles 50%, also #2 Doubles 50% · published
Haddon Wong Yuen
usually #2 Doubles 100% · published
Kuakini Baltero
usually #3 Doubles 50%, also #2 Doubles 33% · published
Nicholas Tran
usually #3 Doubles 100% · published
Reiko Hamano
usually #2 Doubles 50%, also #3 Doubles 25% · 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.

Grant Yamamoto + Liane Martin4255% games−11.3% vs expected
Mark Chun + Kari Wicklund5062% gamesnot enough data
Tomoyuki Furuhata + Reiko Hamano314 matchesnot enough data
Christopher Agpoon + Liane Martin314 matchesnot enough data
Christopher Agpoon + Nikki Ideta224 matchesnot enough data
Michelle Oishi + Kuakini Baltero213 matchesnot enough data
Marissa Hayashi + Kuakini Baltero303 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.

4.5
Tomoyuki Furuhata
23W–9L career · type S · 3 lines in 2022
1%93%6%
4.30
4
Kari Wicklund
43W–13L career · 2 lines in 2022
<1%40%60%
4.03
4
Marissa Hayashi
110W–54L career · 2 lines in 2022
<1%68%32%
3.94
Ryan Liu
20W–14L career · 2 lines in 2022
<1%89%11%
3.84
4
Sheri Kinoshita
179W–143L career · 4 lines in 2022
1%94%5%
3.79
4
Nikki Ideta
41W–30L career · type S · 3 lines in 2022
2%94%4%
3.77
4
Christopher Agpoon
32W–19L career · 4 lines in 2022
not enough data
4
Liane Martin
102W–109L career · 4 lines in 2022
28%71%<1%
3.57
4
Grant Yamamoto
41W–20L career · 2 lines in 2022
32%67%<1%
3.56
4
Michelle Oishi
30W–45L career · 3 lines in 2022
49%51%<1%
3.50
Mark Chun
48W–20L career · 2 lines in 2022
1%93%5%
3.29
Haddon Wong Yuen
40W–11L career · 2 lines in 2022
not enough data
Kuakini Baltero
23W–9L career · 6 lines in 2022
not enough data
Nicholas Tran
7W–1L career · 2 lines in 2022
not enough data
Reiko Hamano
40W–26L career · 4 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.