Teams

SGV Underdogs Titans-Bandaru-Diamond Bar HS/SA10:30

2026 Winter Team Singles · SGV - Men 3.5

9 players · average NTRP 3.50 / SO.CALIFORNIA

View scouting list →
Schedule5 played
L#1 SinglesYijun Zhang vs Sandeep Kamalon7-5, 3-6, 1-0
L#1 SinglesYijun Zhang vs Richard Lie2-6, 6-7
L#2 SinglesAndy Hsieh vs Daniel Herman4-6, 3-6
L#1 SinglesKaran Kajla vs Abraam Guirguis7-5, 5-7, 0-1
L#3 SinglesRussel Segawa vs Thai Nguyen1-6, 3-6
2026-01-24vs SGV Busy Beavers-Lin-CalTech/SU10Lost 01
L#2 SinglesAndy Hsieh vs Han Xu6-3, 0-6, 0-1
2026-01-17vs SGV Padawans-GAMEZ-WN/SA12Lost 01
L#2 SinglesAditya Kajla vs Kirby Xu3-6, 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 standings7 teams · SGV - Men 3.5
TeamWLInd. WInd. LSets lostGames lost
1SGV LLW Heavy Hitters-St Clair-Arcadia/SA14211716140
2SGV Hot Shots Redemption-Nguyen-Palm Park/SA24211718153
3SGV Padawans-GAMEZ-WN/SA124211718167
4SGV Underdogs Titans-Bandaru-Diamond Bar HS/SA10:30339919162
5SGV Underdogs Aces-Ponnaganti/Diamond Bar HS/SA10:3310820167
6SGV Busy Beavers-Lin-CalTech/SU103381023181
7SGV Team Lee-WN/SU20631532201

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 3.05 estimated across 7 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.

Aditya Kajla
usually #2 Singles 100% · published 3.5
Chinna Ponnaganti
published 3.5
3.21
Yijun Zhang
usually #1 Singles 100% · published
3.15
Karan Kajla
usually #1 Singles 100% · published
3.09
Russel Segawa
usually #3 Singles 100% · published
3.03
Balaji Alahari
published 3.5
2.96
Andy Hsieh
usually #2 Singles 100% · published 3.5
2.95
Ramesh Bandaru
published
2.95
Stanley Phu
published
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
Aditya Kajla
1W–3L career · type S · 1 line in 2026
not enough data
3.5
Chinna Ponnaganti
1W–4L career · no lines in 2026
not enough data
Yijun Zhang
11W–23L career · 2 lines in 2026
<1%7%93%
3.21
Karan Kajla
7W–8L career · 1 line in 2026
<1%15%85%
3.15
Russel Segawa
2W–10L career · 1 line in 2026
27%73%<1%
3.09
3.5
Balaji Alahari
5W–6L career · no lines in 2026
43%57%<1%
3.03
3.5
Andy Hsieh
2W–9L career · 2 lines in 2026
63%37%<1%
2.96
Ramesh Bandaru
20W–26L career · no lines in 2026
<1%64%36%
2.95
Stanley Phu
1W–10L career · no lines in 2026
64%36%<1%
2.95

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.