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Oat's Ladies

2023 Fall Combo -2 Sundays · 7.5 Women

2 players · average NTRP 3.75 · USTA/PACIFIC NW / ALASKA

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Scouting

Roster averages 4.28 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.

4.28
Katrina Brown
usually #1 Doubles 100% · published 4.5
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Cheevarat Wongsaree
usually #2 Doubles 67%, also #1 Doubles 33% · published 3
Results4 ties
2022-09-18Split 1–1
W#1 DoublesKatrina Brown / Walaiporn Sukanthanag vs ELIZE Rumley / Denise Henderson5-7, 6-1, 1-0
L#2 DoublesSaharra McKee / Cheevarat Wongsaree vs Dana Griffin / Nicolle Welch3-6, 7-6, 1-0
2022-09-18Won 2–0
W#1 DoublesKatrina Brown / Saharra McKee vs Kima Kimura / Brook Connolly6-1, 6-2
W#2 DoublesEmily Elison / Cheevarat Wongsaree vs Jessie Lief / Daniella DeLozier6-3, 3-6, 1-0
2022-09-11Won 1–0
W#1 DoublesKatrina Brown / Cheevarat Wongsaree vs Rebecca Kinworthy / Triin Minton3-6, 6-4, 1-0
2022-09-11Lost 0–1
L#1 DoublesKatrina Brown / Walaiporn Sukanthanag vs Trena Rairdon / Daniella DeLozier6-4, 7-5
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.

4.5
Katrina Brown
63W–17L career
1%92%7%
4.28
3
Cheevarat Wongsaree
33W–8L career · type M
not enough data
—

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.