Teams

SGV Underdogs Titans-Le-Diamond Bar HS/SU8

2025 SoCal Doubles 18 & Over - San Gabriel Valley · SGV - Men 4.0

13 players · average NTRP 4.00 / SO.CALIFORNIA

View scouting list →
Schedule1 played
L#1 DoublesMark Stone / Tom Le vs Joshua Esparza / Arnold Lopez6-4, 3-6, 0-1
W#2 DoublesSudhagar Subbiyan / Gerald Alphonse vs Oscar De La Rosa / Bill Michels6-4, 6-4
L#3 DoublesEric Chen / Manish Anand vs Vansh Talwar / Robert de la Costa6-7, 5-7
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 - Men 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 3.47 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.

3.74
Allison de Leon
published 4
3.69
3.57
Ronald Legaspi
published
3.56
Mark Stone
usually #1 Doubles 100% · published
3.55
Matthew Huang
published
3.42
Rudy Tatang
usually #1 Doubles 100% · published
3.36
Manish Anand
usually #3 Doubles 100% · published
3.35
Gerald Alphonse
usually #1 Doubles 50%, also #2 Doubles 50% · published
3.22
Ruben Ron
usually #1 Doubles 100% · published
3.21
Oscar Oyama
usually #1 Doubles 100% · published
Gang Dai
published
Jordan Tatang
published
Sudhagar Subbiyan
usually #2 Doubles 100% · 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.

Oscar Oyama + Ruben Ron5160% games+4.2% vs expected
Rudy Tatang + Ruben Ron4352% games+4.1% vs expected
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.

4
Allison de Leon
4W–2L career · no lines in 2025
4%92%3%
3.74
Praveenkumar Devarajan
5W–4L career · no lines in 2025
8%90%1%
3.69
Ronald Legaspi
3W–5L career · no lines in 2025
30%70%<1%
3.57
Mark Stone
9W–5L career · 1 line in 2025
32%68%<1%
3.56
Matthew Huang
4W–3L career · no lines in 2025
37%63%<1%
3.55
Rudy Tatang
13W–10L career · 1 line in 2025
<1%<1%>99%
3.42
Manish Anand
7W–6L career · 2 lines in 2025
1%84%16%
3.36
Gerald Alphonse
22W–6L career · 2 lines in 2025
<1%1%99%
3.35
Ruben Ron
18W–14L career · 1 line in 2025
<1%6%94%
3.22
Oscar Oyama
14W–6L career · 1 line in 2025
<1%6%94%
3.21
Gang Dai
2W–1L career · no lines in 2025
not enough data
Jordan Tatang
1W–1L career · no lines in 2025
not enough data
Sudhagar Subbiyan
3W–1L career · 1 line in 2025
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.