Teams

SGV Mo Better Tennis- DeRosa-WN/SA10

2021 SoCal Doubles 18 & Over - San Gabriel Valley · SGV - Women 4.0

11 players · average NTRP 3.93 / SO.CALIFORNIA

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Schedule3 played
2021-10-24vs SGV Dynamic Duos -Chow-WN/SU10Won 10
W#3 DoublesHolly Lieberenz / Karen Vidal vs Joanna Aguinaldo / Josephine Chow6-1, 6-1
L#3 DoublesPatricia Fagerberg / Kathleen Janisch vs Jane Caldito / DENISE GICK2-6, 6-2, 0-1
W#1 DoublesRoseann DeRosa / Holly Lieberenz vs Rebecca Escandon / Summer Shelton6-1, 7-6
L#3 DoublesElena Salinas / Kathleen Janisch vs Chandler Nguyen / Suzanne Segal2-6, 1-6
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 4.0 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 3.65 estimated across 10 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.

3.89
Karen Vidal
published
3.77
Monique Lind
published 4
3.76
Christina Islas
published 4
3.74
Kelly Moss
published
3.74
Satsuki Yamashita
published
3.73
Roseann DeRosa
published 4
3.71
Theona Zhordania
published 4
3.54
Holly Lieberenz
usually #1 Doubles 80%, also #3 Doubles 20% · published 4
3.48
Elena Salinas
published 4
3.16
Kathleen Janisch
usually #3 Doubles 100% · published 3.5
Tivy Wong
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.

Monique Lind + Theona Zhordania5353% games+4.3% vs expected
Theona Zhordania + Roseann DeRosa191651% games+1.9% vs expected
Holly Lieberenz + Theona Zhordania4647% games−3.9% vs expected
Holly Lieberenz + Roseann DeRosa5457% gamesnot enough data
Roseann DeRosa + Elena Salinas4341% gamesnot enough data
Monique Lind + Roseann DeRosa4257% gamesnot enough data
Kelly Moss + Satsuki Yamashita224 matchesnot enough data
Theona Zhordania + Kelly Moss213 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.

Karen Vidal
25W–10L career · no lines in 2021
<1%81%19%
3.89
4
Monique Lind
54W–39L career · no lines in 2021
2%94%4%
3.77
4
Christina Islas
4W–4L career · no lines in 2021
2%94%3%
3.76
Kelly Moss
8W–8L career · no lines in 2021
3%94%2%
3.74
Satsuki Yamashita
4W–3L career · no lines in 2021
3%94%2%
3.74
4
Roseann DeRosa
162W–106L career · no lines in 2021
4%94%2%
3.73
4
Theona Zhordania
117W–121L career · no lines in 2021
5%93%1%
3.71
4
Holly Lieberenz
168W–125L career · 10 lines in 2021
37%63%<1%
3.54
4
Elena Salinas
140W–158L career · no lines in 2021
55%45%<1%
3.48
3.5
Kathleen Janisch
60W–49L career · 4 lines in 2021
11%88%<1%
3.16
Tivy Wong
1W–1L career · no lines in 2021
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.