Teams

SGV Arcadia Allies-Li--Arcadia-SU1

2025 Mixed Doubles - 18 & Over San Gabriel Valley · SGV - 6.0 Mixed Division

10 players · average NTRP 3.17 / 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 →
Schedule3 played
W#1 DoublesSu Li / Changlin Wu vs Adriana Higuera / Sebastian Perez7-6, 4-6, 1-0
W#2 DoublesJulia Arnold / Jeff Bernstein vs Giovanni Leguizamon / Lisa Santana6-3, 7-6
L#1 DoublesKirby Xu / Xintong Tan vs Sergio Salas / Adriana Higuera4-6, 3-6
W#2 DoublesSu Li / Xiao Zhang vs Sebastian Perez / Ariana Garcia6-4, 6-2
L#3 DoublesChanglin Wu / Barb Vetterick vs Vanessa Vanda / Nicolas Velazco1-6, 6-7
W#1 DoublesKirby Xu / Xintong Tan vs Sergio Salas / Corinda Hayes3-6, 6-3, 1-0
L#2 DoublesBarb Vetterick / Changlin Wu vs Adriana Higuera / Calvin Maniago3-6, 3-6
L#3 DoublesJeff Bernstein / Julia Arnold vs Sebastian Perez / Vanessa Vanda3-6, 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 - 6.0 Mixed Division 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 3.07 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.

3.70
Rachel Brereton
published
3.19
Kirby Xu
usually #1 Doubles 100% · published
3.15
Julia Arnold
usually #2 Doubles 50%, also #3 Doubles 50% · published
3.12
Andy Zang
published 3.5
3.08
Su Li
usually #1 Doubles 50%, also #2 Doubles 50% · published
2.90
Xintong Tan
usually #1 Doubles 100% · published
2.71
Barb Vetterick
usually #2 Doubles 50%, also #3 Doubles 50% · published 3
2.70
Changlin Wu
usually #1 Doubles 33%, also #2 Doubles 33% · published 3
Jeff Bernstein
usually #2 Doubles 50%, also #3 Doubles 50% · published
Kezhi YAN
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.

Kirby Xu + Xintong Tan2643% games+2.2% vs expected
Su Li + Andy Zang4253% gamesnot enough data
Su Li + Changlin Wu134 matchesnot enough data
Changlin Wu + Barb Vetterick033 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.

Rachel Brereton
9W–2L career · no lines in 2025
8%91%2%
3.70
Kirby Xu
14W–16L career · 2 lines in 2025
8%90%1%
3.19
Julia Arnold
33W–10L career · 2 lines in 2025
<1%15%85%
3.15
3.5
Andy Zang
33W–21L career · no lines in 2025
21%79%<1%
3.12
Su Li
32W–26L career · 2 lines in 2025
<1%28%72%
3.08
Xintong Tan
14W–13L career · 2 lines in 2025
<1%77%23%
2.90
3
Barb Vetterick
8W–11L career · 2 lines in 2025
7%91%2%
2.71
3
Changlin Wu
17W–27L career · 3 lines in 2025
8%91%2%
2.70
Jeff Bernstein
1W–1L career · 2 lines in 2025
not enough data
Kezhi YAN
0W–7L career · no lines 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.