Teams

SGV Skyline- Chan - WN/SU10

2022 Mixed Doubles - 40 & Over San Gabriel Valley · SGV - 9.0 Mixed Division

16 players · average NTRP 4.42 / 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 - 9.0 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 3.98 estimated across 13 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.

4.35
Tai Sisson
usually #2 Doubles 63%, also #1 Doubles 25% · published 4.5
4.35
Kristina Chen
usually #2 Doubles 50%, also #1 Doubles 25% · published 4.5
4.24
Tricia Guinto
usually #3 Doubles 50%, also #1 Doubles 50% · published 4.5
4.15
Jennifer Avila
published
4.11
Gamble Yeung
published 4.5
4.05
Ky Vo
published
4.01
Roseann Harris
usually #2 Doubles 100% · published 4.5
4.00
Jesse Huang
published
3.87
Michael Tschebaum
published
3.87
Wenli Chen
published
3.70
Lorna Kim
usually #1 Doubles 100% · published 4
3.54
Jonathan Mak
published
3.44
Karen Obst
published
Jesse Wallis
published
Levinhduc Nguyen
published
Matt Jester
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.

Matt Jester + Kristina Chen044 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.

4.5
Tai Sisson
249W–74L career · 8 lines in 2022
<1%87%13%
4.35
4.5
Kristina Chen
152W–92L career · 4 lines in 2022
<1%87%12%
4.35
4.5
Tricia Guinto
124W–84L career · 2 lines in 2022
3%94%2%
4.24
Jennifer Avila
8W–3L career · no lines in 2022
12%88%<1%
4.15
4.5
Gamble Yeung
1W–3L career · no lines in 2022
20%80%<1%
4.11
Ky Vo
11W–15L career · no lines in 2022
35%65%<1%
4.05
4.5
Roseann Harris
96W–74L career · 1 line in 2022
46%54%<1%
4.01
Jesse Huang
16W–13L career · no lines in 2022
48%52%<1%
4.00
Michael Tschebaum
5W–4L career · no lines in 2022
<1%<1%>99%
3.87
Wenli Chen
5W–10L career · no lines in 2022
85%15%<1%
3.87
4
Lorna Kim
210W–162L career · 1 line in 2022
6%93%1%
3.70
Jonathan Mak
3W–6L career · no lines in 2022
36%64%<1%
3.54
Karen Obst
0W–5L career · no lines in 2022
67%33%<1%
3.44
Jesse Wallis
1W–0L career · no lines in 2022
not enough data
Levinhduc Nguyen
1W–1L career · no lines in 2022
not enough data
Matt Jester
0W–5L 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.