Teams

OC - Eternals Assemble - LPC - Emily

2022 USTA Mixed Doubles 18 & Over - OC · OC - 9.0 WE - Weekend Mixed Doubles

14 players · average NTRP 4.64 / SO.CALIFORNIA

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 →
Schedule3 played
2022-03-12vs OC - LPC - Sally -Won 10
W#3 DoublesDaniel Keolasy / Rachel Om vs Sally Namie / Don Pham6-3, 6-4
2022-01-30Lost 01
L#2 DoublesDaniel Keolasy / Rachel Om vs Eric Nguyen / Christine Lee3-6, 2-6
2022-01-22vs OC Mixed Troubles - LNRC - MehtaWon 10
W#2 DoublesDaniel Keolasy / Rachel Om vs Alissa Ahlman / Vishal Patel3-6, 6-0, 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 standings for OC - 9.0 WE - Weekend Mixed Doubles 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 4.24 estimated across 12 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.

4.86
David Eiges
published 5
4.81
Quynh Le
published
4.71
Daniel Keolasy
published 5
4.67
Emily Wu
published 5
4.38
Ariel Lee
published 4.5
4.24
Emily Lu
published 4.5
4.07
Michelle Hay
published
4.04
Rachel Om
usually #2 Doubles 67%, also #3 Doubles 33% · published 4
3.90
Jerikko Timm Agatep
published 4.5
3.81
Rex Sheng
published
3.70
Victor Wu
published
3.69
Katie Moore
published
Lawrence Chan
published
Suzanne Lin
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.

Daniel Keolasy + Rachel Om13174% games+22.2% vs expected
Emily Wu + Victor Wu0536% gamesnot 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.

5
David Eiges
5W–0L career · no lines in 2022
<1%86%14%
4.86
Quynh Le
12W–6L career · no lines in 2022
1%92%7%
4.81
5
Daniel Keolasy
14W–15L career · no lines in 2022
5%94%1%
4.71
5
Emily Wu
2W–12L career · no lines in 2022
10%90%1%
4.67
4.5
Ariel Lee
10W–6L career · no lines in 2022
<1%82%18%
4.38
4.5
Emily Lu
22W–25L career · no lines in 2022
3%94%2%
4.24
Michelle Hay
2W–7L career · no lines in 2022
29%71%<1%
4.07
4
Rachel Om
166W–64L career · 3 lines in 2022
<1%38%62%
4.04
4.5
Jerikko Timm Agatep
30W–21L career · no lines in 2022
78%22%<1%
3.90
Rex Sheng
7W–8L career · no lines in 2022
1%92%7%
3.81
Victor Wu
3W–7L career · no lines in 2022
6%93%1%
3.70
Katie Moore
3W–8L career · no lines in 2022
>99%<1%0%
3.69
Lawrence Chan
5W–7L career · no lines in 2022
not enough data
Suzanne Lin
1W–1L career · no 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.