Teams

SGV LLW Glowing Aceholes-Tsai-Arroyo High/SA8

2025 Tri-Level League - San Gabriel Valley · SGV - Women 2.5

16 players · average NTRP 3.25 / SO.CALIFORNIA

View scouting list →
Schedule2 played
2025-08-24Won 10
W#1 DoublesMelissa Lor / Jenniffer Wong vs N/A6-0, 6-0
W#1 DoublesJenniffer Wong / Tracy Lee vs Ariana Garcia / Paula Quesada6-1, 4-6, 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 SGV - Women 2.5 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 3.06 estimated across 15 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.

3.54
Michelle Wong
published
3.43
Sherie Paulson
usually #2 Doubles 44%, also #1 Doubles 33% · published 3.5
3.40
Claire Rifelj
published 3.5
3.37
Debbie Maringka
published 3.5
3.33
Jenniffer Wong
usually #1 Doubles 100% · published 3.5
3.30
Melissa Lor
published
3.17
Jennifer Sung
published
3.13
Regina Cheung
published
2.99
Cynthia Su
published 3
2.89
Amy Soong Tsai
usually #3 Doubles 50%, also #2 Doubles 38% · published 3
2.88
Christine Pedroza
usually #3 Doubles 75%, also #2 Doubles 25% · published 3
2.84
Jackie Yi
usually #3 Doubles 100% · published 3
2.77
Homa Alamdari
published
2.57
Tina Lu
published
2.33
Jennifer Win
published
Jamie Chu
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.

Regina Cheung + Sherie Paulson5158% gamesnot enough data
Sherie Paulson + Michelle Wong404 matchesnot enough data
Debbie Maringka + Michelle Wong404 matchesnot enough data
Jackie Yi + Cynthia Su134 matchesnot enough data
Cynthia Su + Tina Lu224 matchesnot enough data
Sherie Paulson + Claire Rifelj123 matchesnot enough data
Jennifer Sung + Debbie Maringka213 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.

Michelle Wong
23W–7L career · no lines in 2025
0%<1%>99%
3.54
3.5
Sherie Paulson
102W–61L career · 9 lines in 2025
<1%69%31%
3.43
3.5
Claire Rifelj
34W–11L career · no lines in 2025
<1%77%23%
3.40
3.5
Debbie Maringka
27W–8L career · no lines in 2025
<1%81%18%
3.37
3.5
Jenniffer Wong
200W–169L career · 2 lines in 2025
1%88%11%
3.33
Melissa Lor
14W–8L career · no lines in 2025
2%91%8%
3.30
Jennifer Sung
19W–11L career · no lines in 2025
11%88%1%
3.17
Regina Cheung
9W–12L career · no lines in 2025
<1%17%83%
3.13
3
Cynthia Su
30W–17L career · no lines in 2025
<1%54%46%
2.99
3
Amy Soong Tsai
89W–60L career · 8 lines in 2025
<1%79%21%
2.89
3
Christine Pedroza
39W–40L career · 4 lines in 2025
<1%80%20%
2.88
3
Jackie Yi
39W–37L career · 1 line in 2025
1%87%12%
2.84
Homa Alamdari
23W–10L career · no lines in 2025
3%92%5%
2.77
Tina Lu
23W–22L career · no lines in 2025
0%31%69%
2.57
Jennifer Win
11W–7L career · no lines in 2025
0%88%12%
2.33
Jamie Chu
1W–0L career · no lines in 2025
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.