Teams

SGV Mo Better Tri-DeRosa-WN/SU8

2023 Tri-Level League - San Gabriel Valley · SGV - Women 3.5

16 players · average NTRP 4.09 / SO.CALIFORNIA

View scouting list →
Schedule2 played
W#1 DoublesMaria O'Connor / Loretta Peng vs Katherine Wu / Mandi Collier3-2
W#2 DoublesRoseann DeRosa / Theona Zhordania vs Stephanie Perry / Cindi Carter7-5, 6-4
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 3.5 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 3.81 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.

4.40
Chandler Nguyen
published 4.5
4.29
Maria O'Connor
usually #1 Doubles 100% · published 4.5
4.18
Emily Marmol
published 4.5
4.15
Jennifer Avila
published
3.86
Claudia Ibarra
published 4
3.80
Xiaochun Wang
published
3.77
Monique Lind
usually #1 Doubles 100% · published 4
3.76
Christina Islas
published 4
3.73
Roseann DeRosa
usually #2 Doubles 100% · published 4
3.71
Theona Zhordania
usually #2 Doubles 100% · published 4
3.61
Serena Tseng
usually #2 Doubles 75%, also #3 Doubles 25% · published 4
3.48
Elena Salinas
published 4
3.36
Tina Yang
published
3.26
Diane Quan
published 3.5
Julia Sargsyan
published
Loretta Peng
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.

Claudia Ibarra + Elena Salinas20459% games+6.5% vs expected
Claudia Ibarra + Roseann DeRosa11952% games+4.8% vs expected
Monique Lind + Theona Zhordania5353% games+4.3% vs expected
Theona Zhordania + Roseann DeRosa191651% games+1.9% vs expected
Claudia Ibarra + Theona Zhordania6358% gamesnot enough data
Roseann DeRosa + Elena Salinas4341% gamesnot enough data
Monique Lind + Roseann DeRosa4257% gamesnot enough data
Monique Lind + Claudia Ibarra4159% gamesnot 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
Chandler Nguyen
18W–7L career · no lines in 2023
<1%78%22%
4.40
4.5
Maria O'Connor
48W–39L career · 1 line in 2023
1%93%5%
4.29
4.5
Emily Marmol
3W–3L career · no lines in 2023
8%91%1%
4.18
Jennifer Avila
8W–3L career · no lines in 2023
12%88%<1%
4.15
4
Claudia Ibarra
97W–62L career · no lines in 2023
<1%86%13%
3.86
Xiaochun Wang
4W–0L career · no lines in 2023
1%93%6%
3.80
4
Monique Lind
54W–39L career · 4 lines in 2023
2%94%4%
3.77
4
Christina Islas
4W–4L career · no lines in 2023
2%94%3%
3.76
4
Roseann DeRosa
162W–106L career · 3 lines in 2023
4%94%2%
3.73
4
Theona Zhordania
117W–121L career · 1 line in 2023
5%93%1%
3.71
4
Serena Tseng
54W–35L career · 4 lines in 2023
20%80%<1%
3.61
4
Elena Salinas
140W–158L career · no lines in 2023
55%45%<1%
3.48
Tina Yang
10W–6L career · no lines in 2023
<1%86%14%
3.36
3.5
Diane Quan
6W–13L career · no lines in 2023
2%95%3%
3.26
Julia Sargsyan
1W–1L career · no lines in 2023
not enough data
Loretta Peng
0W–2L 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.