Teams

SGV Mo Better Mixed-De Rosa-WN/SA12

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

13 players · average NTRP 4.14 / 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 3.80 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.

4.15
Jennifer Avila
published
4.14
Austin Galliguez
published 4.5
4.08
Shirley Fong
usually #1 Doubles 100% · published 4.5
3.83
Jonathan Talbot
published
3.78
Xiaochun Wang
published
3.70
Roseann DeRosa
usually #1 Doubles 57%, also #2 Doubles 29% · published 4
3.68
Theona Zhordania
usually #2 Doubles 100% · published 4
3.68
Charmaine Felix-Meyer
usually #3 Doubles 57%, also #1 Doubles 29% · published 4
3.67
Clement Chan
published 4
3.56
Martin Vasquez
published
3.48
Elena Salinas
published 4
Everjohn Feliciano
published
Jefferson Law
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.

Charmaine Felix-Meyer + Jonathan Talbot033 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.

Jennifer Avila
8W–3L career · no lines in 2023
14%85%1%
4.15
4.5
Austin Galliguez
6W–4L career · no lines in 2023
16%84%1%
4.14
4.5
Shirley Fong
89W–47L career · 1 line in 2023
27%72%<1%
4.08
Jonathan Talbot
5W–7L career · no lines in 2023
1%88%11%
3.83
Xiaochun Wang
4W–0L career · no lines in 2023
2%92%5%
3.78
4
Roseann DeRosa
162W–106L career · 7 lines in 2023
8%91%2%
3.70
4
Theona Zhordania
117W–121L career · 3 lines in 2023
10%89%1%
3.68
4
Charmaine Felix-Meyer
118W–128L career · 7 lines in 2023
10%89%1%
3.68
4
Clement Chan
8W–5L career · no lines in 2023
11%88%1%
3.67
Martin Vasquez
4W–3L career · no lines in 2023
<1%33%67%
3.56
4
Elena Salinas
140W–158L career · no lines in 2023
55%45%<1%
3.48
Everjohn Feliciano
2W–0L career · no lines in 2023
not enough data
Jefferson Law
1W–0L 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.