Teams

LLW SGV Wild Cards-Tang-Arroyo HS/SU9

2023 Mixed Doubles - 40 & Over San Gabriel Valley · SGV - 8.0 Mixed Division

16 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 3.96 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.

Eugene Shin
published 5
4.54
Karen Char
usually #3 Doubles 50%, also #2 Doubles 50% · published 5
4.42
Cindy Shin
published 4.5
4.27
Colin Tang
published 4
4.25
Hank Gwon
published 4.5
4.13
Hatty Yip
usually #2 Doubles 50%, also #1 Doubles 50% · published 4
4.00
Jesse Huang
published
3.87
Daniel Kanemoto
published 4
3.80
William Ko
published
Cristine Kim
published 4
3.74
Kasia Chmielewski
published
3.62
Jeffery Kam
published 3.5
3.42
Jasmine M Liu
published
3.40
Laurie Manley
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.

Jeffery Kam + Karen Char9355% games−5.3% vs expected
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.

5
Eugene Shin
4W–4L career · no lines in 2023
not enough data
5
Karen Char
225W–84L career · 2 lines in 2023
36%64%<1%
4.54
4.5
Cindy Shin
11W–8L career · no lines in 2023
<1%73%27%
4.42
4
Colin Tang
17W–2L career · no lines in 2023
<1%2%98%
4.27
4.5
Hank Gwon
3W–3L career · type M · no lines in 2023
3%95%3%
4.25
4
Hatty Yip
99W–33L career · 4 lines in 2023
<1%16%84%
4.13
Jesse Huang
16W–13L career · no lines in 2023
48%52%<1%
4.00
4
Daniel Kanemoto
23W–13L career · no lines in 2023
<1%84%16%
3.87
William Ko
3W–2L career · no lines in 2023
1%93%6%
3.80
4
Charles Villarino
0W–1L career · no lines in 2023
not enough data
4
Cristine Kim
1W–0L career · no lines in 2023
not enough data
Kasia Chmielewski
9W–12L career · no lines in 2023
3%94%2%
3.74
3.5
Jeffery Kam
148W–117L career · type A · no lines in 2023
<1%18%82%
3.62
Jasmine M Liu
22W–8L career · no lines in 2023
<1%74%26%
3.42
Laurie Manley
8W–9L career · no lines in 2023
77%23%<1%
3.40
Robert Birmingham
4W–4L career · no lines in 2023
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.