Teams

Doubles Divas

2026 Tri-One Doubles League · 3.0 Women

6 players · average NTRP 3.00 / OAHU

View scouting list →
Schedule9 played
2026-08-23vs Bad News BunniesWon 10
W#1 DoublesRosalynne Kakogawa-Wong / Darlene Chang vs Sonavie Ong / Allison Gough6-4, 3-6, 1-0
2026-08-08vs Kuliouou Double TroubleWon 10
W#1 DoublesJennifer Ostachuk / Terri Mei vs Akiko Ooi / Susan Shintani6-1, 6-0
2026-08-02vs OC BestiesWon 10
W#1 DoublesShana Suzuki / Gayle Hatakeyama vs Ani Dinkova / Lydia Yabsley6-1, 7-5
2026-08-01vs OC BestiesWon 10
W#1 DoublesGayle Hatakeyama / Terri Mei vs Lydia Yabsley / Novajocymarie Nishida6-1, 6-1
2026-07-25vs LUV-LUVLost 01
L#1 DoublesJennifer Ostachuk / Terri Mei vs Rumiko Wong / Sharon Vidal2-6, 3-6
2026-07-18vs JustLuvTennis 3.0Won 10
W#1 DoublesRosalynne Kakogawa-Wong / Darlene Chang vs Xiaofei Mai / June Chung7-5, 7-6
2026-07-12vs OC Sparkly Powerpuff SquadWon 10
W#1 DoublesShana Suzuki / Darlene Chang vs Christine KIm / Keiko Kratky7-6, 6-0
2026-06-28vs Bad News BunniesWon 10
W#1 DoublesJennifer Ostachuk / Terri Mei vs Sonavie Ong / Maria Wisco6-0, 6-1
2026-06-21vs Kuliouou Double TroubleWon 10
W#1 DoublesShana Suzuki / Rosalynne Kakogawa-Wong vs Shina Degucci / Susan Shintani6-1, 6-2
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 standings for 3.0 Women 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 2.89 estimated across 6 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.

2.99
Gayle Hatakeyama
usually #1 Doubles 100% · published 3
2.90
Rosalynne Kakogawa-Wong
usually #1 Doubles 100% · published 3
2.89
Terri Mei
usually #1 Doubles 100% · published 3
2.87
Jennifer Ostachuk
usually #1 Doubles 100% · published 3
2.87
Shana Suzuki
usually #1 Doubles 100% · published 3
2.83
Darlene Chang
usually #1 Doubles 100% · published 3
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.

Terri Mei + Gayle Hatakeyama4359% games+7.1% vs expected
Shana Suzuki + Darlene Chang7552% games−1.7% vs expected
Shana Suzuki + Terri Mei033 matchesnot enough data
Jennifer Ostachuk + Terri Mei213 matchesnot enough data
Jennifer Ostachuk + Darlene Chang123 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.

3
Gayle Hatakeyama
47W–25L career · 2 lines in 2026
<1%52%48%
2.99
3
Rosalynne Kakogawa-Wong
39W–84L career · 3 lines in 2026
<1%76%24%
2.90
3
Terri Mei
55W–65L career · 4 lines in 2026
<1%78%22%
2.89
3
Jennifer Ostachuk
82W–83L career · 3 lines in 2026
<1%82%17%
2.87
3
Shana Suzuki
95W–105L career · 3 lines in 2026
<1%83%17%
2.87
3
Darlene Chang
93W–86L career · 3 lines in 2026
1%87%12%
2.83

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.