Teams

SDNC LLW 7.0 RBS&T/ Madden

2022 Mixed Doubles 18 & Over Winter- SDNC · SDNC - 7.0

11 players · average NTRP 3.88 / SAN DIEGO

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 →
Schedule6 played
L#1 DoublesSeiichi Adachi / Alissa Ly vs Angela Verdenacci / Matthew Liu3-6, 3-6
2022-02-26vs SDNC 7.0 Rancho Santa Fe TC/ LindseySplit 11
L#1 DoublesAnil Arcalgud / Lara Mannell vs Anne Case / Tom Vu4-6, 4-6
W#2 DoublesAlissa Ly / Seiichi Adachi vs Tricia Bothmer / Mark Lindsey6-2, 6-2
2022-02-12vs SDNC 7.0 Rancho Santa Fe/ BastiasWon 10
W#2 DoublesMarc Kieu / Alissa Ly vs Katherine Nakamura / Kristoffer Lund6-1, 6-2
2022-02-05vs SDNC 7.0 RPTC/ TaillacWon 10
W#3 DoublesLara Mannell / Marc Kieu vs Pat Greenwald / Dan Taillac6-2, 6-3
L#2 DoublesLara Mannell / Marc Kieu vs Annie Ruttenber / Robert Picunko4-6, 5-7
2022-01-22Won 10
W#1 DoublesSeiichi Adachi / Alissa Ly vs Jay Schram / Kathleen Kleinfeld6-3, 6-2
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 SDNC - 7.0 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 3.62 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.

3.91
Michael Zhou
published
3.83
Marc Kieu
usually #2 Doubles 67%, also #3 Doubles 33% · published 4
3.75
Steven Hoang
published
3.75
Alissa Ly
usually #1 Doubles 50%, also #2 Doubles 50% · published 4
3.64
Joy Madden
published
3.60
Joan Rogers
published
3.52
Sun Lee
published
3.51
Anil Arcalgud
usually #1 Doubles 100% · published 4
3.37
Satheesh Kandavelu
published
3.26
Lara Mannell
published 3.5
Kenneth Lee
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.

Lara Mannell + Kenneth Lee213 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.

Michael Zhou
4W–4L career · no lines in 2022
<1%76%23%
3.91
4
Marc Kieu
24W–19L career · 3 lines in 2022
1%90%10%
3.83
Steven Hoang
4W–3L career · no lines in 2022
2%95%3%
3.75
4
Alissa Ly
160W–70L career · 4 lines in 2022
3%95%2%
3.75
Joy Madden
1W–4L career · no lines in 2022
14%86%<1%
3.64
Joan Rogers
4W–2L career · no lines in 2022
21%79%<1%
3.60
Sun Lee
18W–20L career · no lines in 2022
43%57%<1%
3.52
4
Anil Arcalgud
19W–41L career · 1 line in 2022
47%53%<1%
3.51
Satheesh Kandavelu
6W–3L career · no lines in 2022
<1%83%16%
3.37
3.5
Lara Mannell
46W–76L career · no lines in 2022
2%94%3%
3.26
Kenneth Lee
7W–1L career · no lines in 2022
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.