Teams

SoCal/Tang/Mixed40&Over8.0

2024 Mixed Doubles - 40 & Over San Gabriel Valley · SGV - 8.0 Mixed Division

17 players · average NTRP 4.25 / 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 →

Flight standings for SGV - 8.0 Mixed Division 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 3.89 estimated across 14 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.

4.46
Jinna Johnson
published
4.43
EDWARD CHOI
published
4.39
Daniela Chung
published 4.5
4.32
Tai Sisson
usually #1 Doubles 75%, also #3 Doubles 25% · published 4.5
4.22
Colin Tang
published 4
4.21
Eugene Tran
published
3.76
Marites Killion
usually #1 Doubles 50%, also #2 Doubles 50% · published 4
3.70
Jesse Huang
published
3.65
Judy Su
published
3.63
Madeline Chang
published
3.53
Jonathan Mak
published
3.46
Laurie Manley
published
3.40
Jasmine M Liu
published
3.38
Hairong Cusack
published
Jacob Shin
published
Jun Young Kim
published
Robert Birmingham
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.

Jun Young Kim + Hairong Cusack4162% gamesnot enough data
Jesse Huang + Jasmine M Liu314 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.

Jinna Johnson
0W–6L career · no lines in 2024
no projection at this level
4.46
EDWARD CHOI
4W–9L career · no lines in 2024
no projection at this level
4.43
4.5
Daniela Chung
65W–27L career · no lines in 2024
<1%78%21%
4.39
4.5
Tai Sisson
249W–74L career · 4 lines in 2024
1%89%9%
4.32
4
Colin Tang
17W–2L career · no lines in 2024
<1%6%94%
4.22
Eugene Tran
5W–9L career · no lines in 2024
<1%7%93%
4.21
4
Marites Killion
115W–68L career · 4 lines in 2024
3%93%4%
3.76
Jesse Huang
16W–13L career · no lines in 2024
<1%8%92%
3.70
Judy Su
11W–7L career · no lines in 2024
<1%<1%>99%
3.65
Madeline Chang
27W–4L career · no lines in 2024
<1%<1%>99%
3.63
Jonathan Mak
3W–6L career · no lines in 2024
42%58%<1%
3.53
Laurie Manley
8W–9L career · no lines in 2024
61%39%<1%
3.46
Jasmine M Liu
22W–8L career · no lines in 2024
<1%77%23%
3.40
Hairong Cusack
17W–11L career · no lines in 2024
<1%<1%>99%
3.38
Jacob Shin
1W–1L career · no lines in 2024
not enough data
Jun Young Kim
10W–1L career · no lines in 2024
not enough data
Robert Birmingham
4W–4L career · no lines in 2024
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.