Teams

SGV Tennis Addicts- Tsai-Arroyo HS/SU8

2026 SoCal Doubles 18 & Over - San Gabriel Valley · SGV - Women 3.5

11 players · average NTRP 3.33 / 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 standings9 teams · SGV - Women 3.5
TeamWLInd. WInd. LSets lostGames lost
1SGV Queens of the Court-Yu-Arroyo Seco/SU4000000
2SGV Ball Hogs-Yip-Arroyo Seco/ SU2000000
3SGV Tennis Addicts- Tsai-Arroyo HS/SU8000000
4SGV Chow Fun- Chow-Arcadia-SA11000000
5SGV FLoBS-Galvagni-Scholl CYN/SU8000000
6SGV Spinners-Hegelund-Flint Cyn/SA12000000
7SGV Canyon Rollers-Shimizu-Freemont Park/SU000000
8SGV Ace Kickers-Hawkins-Claremont Club/SU11000000
9SGV Sloppy Topspin-Higuera-Downey HS/SA 8000000

Ordered by team wins, then losses, then sets lost — the order USTA uses to seed a flight. Individual wins are lines, not ties.

See the full flight, with every team’s record

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 3.27 estimated across 11 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.

3.75
Tina Gong
published
3.73
Michelle Wong
published
3.45
Hoan Tiffany Lau
published 3.5
3.43
Sherie Paulson
published 3.5
3.31
Debbie Maringka
published 3.5
3.29
Melissa Lor
published
3.25
Regina Cheung
published
3.05
Lilly Shuton
published 3.5
2.97
Sonia Chan
published
2.89
Amy Soong Tsai
published 3
2.86
Aline MacK
published 3
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.

Regina Cheung + Sherie Paulson5158% gamesnot enough data
Sherie Paulson + Michelle Wong404 matchesnot enough data
Debbie Maringka + Michelle Wong404 matchesnot enough data
Melissa Lor + Lilly Shuton033 matchesnot enough data
Lilly Shuton + Hoan Tiffany Lau213 matchesnot enough data
Tina Gong + Michelle Wong303 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.

Tina Gong
9W–3L career · no lines in 2026
3%95%3%
3.75
Michelle Wong
23W–7L career · no lines in 2026
<1%4%96%
3.73
3.5
Hoan Tiffany Lau
22W–8L career · type S · no lines in 2026
<1%65%35%
3.45
3.5
Sherie Paulson
102W–61L career · no lines in 2026
<1%71%29%
3.43
3.5
Debbie Maringka
27W–9L career · no lines in 2026
1%92%7%
3.31
Melissa Lor
14W–8L career · no lines in 2026
1%93%5%
3.29
Regina Cheung
9W–12L career · no lines in 2026
3%95%3%
3.25
3.5
Lilly Shuton
90W–82L career · no lines in 2026
35%65%<1%
3.05
Sonia Chan
20W–5L career · no lines in 2026
<1%59%41%
2.97
3
Amy Soong Tsai
89W–60L career · no lines in 2026
<1%80%19%
2.89
3
Aline MacK
71W–56L career · no lines in 2026
<1%86%14%
2.86

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.