Teams

SD 3.0 Slamajamas @BTC/ Kemery

2026 SoCal Fall Doubles WE- San Diego · SD Men 3.0

14 players · average NTRP 3.00 / 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 →
Flight standings7 teams · SD Men 3.0
TeamWLInd. WInd. LSets lostGames lost
1SD 3.0 Mtn View/ Bonillas000000
2SD 3.0 Slamajamas @BTC/ Kemery000000
3SD 3.0 Balboa TC/ Granali-Agra- pending000000
4SD 3.0 Peninsula TC/ Hagopian000000
5SDNC 3.0 UCRC/ Beutler000000
6SD 3.0 BTC team #4- no courts000000
7SDNC 3.0 Baseline Bandits FRCC/ Myers000000

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 2.90 estimated across 12 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.

3.17
Spondee Shenn
published
3.09
Matt Halpin
published 3
3.06
Samer Marroki
published
2.97
Alexander Tunley
published 3
2.96
Jesse Nagelberg
published
2.87
Laljeet Mann
published
2.82
Jason Sophian
published
2.81
Charles Hsien
published 3
2.81
Moe I
published
2.79
Jonathan Janawitz
published
Christopher Chen
published 3
2.75
Joseph Kemery Jr
published 3
2.72
Michael Karim
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.

Matt Halpin + Michael Chaiwimol3348% games+4.8% vs expected
Michael Chaiwimol + Joseph Kemery Jr134 matchesnot enough data
Joseph Kemery Jr + Alexander Tunley314 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.

Spondee Shenn
22W–20L career · no lines in 2026
<1%12%88%
3.17
3
Matt Halpin
78W–39L career · no lines in 2026
<1%27%73%
3.09
Samer Marroki
3W–10L career · no lines in 2026
<1%35%65%
3.06
3
Alexander Tunley
33W–19L career · no lines in 2026
<1%59%41%
2.97
Jesse Nagelberg
7W–3L career · no lines in 2026
<1%60%40%
2.96
Laljeet Mann
5W–5L career · no lines in 2026
<1%82%18%
2.87
Jason Sophian
16W–16L career · no lines in 2026
1%89%9%
2.82
3
Charles Hsien
7W–2L career · no lines in 2026
1%90%9%
2.81
Moe I
3W–0L career · no lines in 2026
1%90%9%
2.81
Jonathan Janawitz
8W–11L career · no lines in 2026
2%91%7%
2.79
3
Christopher Chen
2W–0L career · type A · no lines in 2026
not enough data
3
Joseph Kemery Jr
22W–39L career · no lines in 2026
4%93%3%
2.75
3
Michael Chaiwimol
45W–51L career · no lines in 2026
6%92%2%
2.72
Michael Karim
0W–9L 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.