Teams

SGV Underdogs Aces-Luzzi-Diamond Bar HS/SU8

2026 SoCal Doubles 18 & Over - San Gabriel Valley · SGV - Men 3.5

9 players · average NTRP 3.50 / 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 standings7 teams · SGV - Men 3.5
TeamWLInd. WInd. LSets lostGames lost
1SGV Band of Brothers-Buckwalter-ATCC/SU1000000
2SGV Underdogs Aces-Luzzi-Diamond Bar HS/SU8000000
3SGV Dare Doubles-Pang-WN/SU10000000
4SGV Ball Hogs- R.Yip-Arroyo Seco/ TBD000000
5SGV Underdogs Titans-Bandaru-Diamond Bar HS/SA10:3000000
6SGV Heavy Hitters-St Clair-Arcadia/SU11000000
7SGV The B Team-Nydam-ATCC/SA4000000

Ordered by team wins, then losses, then sets lost — the order USTA uses to seed a flight. Individual wins are lines, not ties.

See the full flight, with every team’s record

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 3.29 estimated across 8 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.

3.41
David Shin
published 3.5
3.38
Pavan Akkimsetty
published
3.35
Gerald Alphonse
published
3.29
Chun Li
published 3.5
3.27
Rajasekar Ramasamy
published
3.24
Joseph Luzzi
published
3.21
Oscar Oyama
published
3.15
Ted Shen
published
Robert Julin
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.

Rajasekar Ramasamy + Chun Li4261% games−0.2% vs expected
David Shin + Ted Shen5164% gamesnot enough data
Joseph Luzzi + Rajasekar Ramasamy123 matchesnot enough data
Joseph Luzzi + Ted Shen213 matchesnot enough data
Gerald Alphonse + Oscar Oyama303 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.

3.5
David Shin
16W–15L career · no lines in 2026
<1%74%26%
3.41
Pavan Akkimsetty
10W–7L career · no lines in 2026
<1%80%20%
3.38
Gerald Alphonse
22W–6L career · no lines in 2026
<1%1%99%
3.35
3.5
Chun Li
7W–3L career · type S · no lines in 2026
2%91%7%
3.29
Rajasekar Ramasamy
6W–5L career · no lines in 2026
3%92%5%
3.27
Joseph Luzzi
9W–11L career · no lines in 2026
4%93%3%
3.24
Oscar Oyama
14W–6L career · no lines in 2026
<1%6%94%
3.21
Ted Shen
21W–16L career · no lines in 2026
<1%14%86%
3.15
Robert Julin
0W–2L career · no lines in 2026
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.