Teams

Lee

2023 One Doubles · 4.0 Women

1 players · average NTRP 4 · USTA/PACIFIC NW / NORTHERN OREGON

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Scouting

Roster averages 3.58 estimated across 1 rated player. 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.

3.58
Dongju Won
usually #1 Doubles 100% · published 4
Results8 ties
2023-08-02Lost 01
L#1 DoublesAngie Lee / Dongju Won vs Amy Bucher / Shannon Roarke4-6, 6-0, 1-0
2023-07-26Won 10
W#1 DoublesAngie Lee / Dongju Won vs Whitney Palfreyman / Jeanette Thomas6-3, 6-4
2023-07-19Won 10
W#1 DoublesAngie Lee / Dongju Won vs Jessica Khalili / Molly Murphy4-6, 7-6, 1-0
2023-07-14Lost 01
L#1 DoublesAngie Lee / Dongju Won vs Kristie Leake / Teresa Sullivan1-6, 6-4, 1-0
2023-07-07Lost 01
L#1 DoublesAngie Lee / Dongju Won vs Courtney Pierce / Claire Bell6-2, 6-1
2023-06-30Won 10
W#1 DoublesAngie Lee / Dongju Won vs Nancy Atkins / Kathleen Budnick6-3, 4-6, 1-0
2023-06-28Won 10
W#1 DoublesAngie Lee / Dongju Won vs Jeanette Thomas / Susie Jansky6-1, 2-0
2023-06-23Won 10
W#1 DoublesAngie Lee / Dongju Won vs Suzanne Boss / Sarah Grewe6-2, 6-3
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.
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.

4
Dongju Won
67W–50L career
16%84%0%
3.58

Three percentages are the year-end projection — chance of moving down, staying, moving up — and the number on the right is our estimated dynamic rating, which USTA never publishes. 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.