Teams

GEPTA/Tri-level/4.0-3.0W/woo#7

SouthernNewMexico · 2026 TRI-LEVEL LEAGUE

10 players · average NTRP 3.33 / GEPTA

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Flight standings7 teams · 2026 TRI-LEVEL LEAGUE
TeamWLInd. WInd. LSets lostGames lost
1GEPTA/Tri-level/4.0-3.0W/woo#7000000
2GEPTA/Tri-level/4.0-3.0W/Molina#6000000
3GEPTA/Tri-level/4.0-3.0W/Baeza#1000000
4GEPTA/Tri-level/4.0-3.0W/Caire#2000000
5GEPTA/Tri-level/4.0-3.0W/Cartwright#3000000
6GEPTA/Tri-level/4.0-3.0W/Martinez#5000000
7GEPTA/Tri-level/4.0-3.0W/Colbert#4000000

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 3.16 estimated across 3 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.

3.48
Gabriela Stoiber
usually #1 Doubles 50%, also #2 Doubles 28% · published 3.5
3.32
Helga Sauza
usually #1 Doubles 27%, also #1 Singles 23% · published 3.5
2.68
Cristina da Costa
usually #2 Doubles 28%, also #3 Doubles 24% · published 3
Jeanette Tan
usually #3 Doubles 60%, also #1 Doubles 30% · published
Jennifer Woo
usually #2 Doubles 47%, also #1 Doubles 41% · published
Lori Armendariz
usually #2 Doubles 48%, also #1 Doubles 37% · published
Patricia Moye Holderman
usually #2 Doubles 70%, also #1 Doubles 30% · published
Rose Rivera
usually #2 Doubles 55%, also #1 Doubles 36% · published
Sonia Rangel
usually #3 Doubles 46%, also #1 Doubles 36% · published
Stephanie Kwan
usually #1 Doubles 60%, also #3 Doubles 40% · 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.

Lori Armendariz + Helga Sauza3255% games+8.0% vs expected
Stephanie Kwan + Jennifer Woo101049% games−8.4% vs expected
Cristina da Costa + Patricia Moye Holderman6456% gamesnot enough data
Lori Armendariz + Patricia Moye Holderman7075% gamesnot enough data
Jeanette Tan + Jennifer Woo123 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
Gabriela Stoiber
65W–58L career · 36 lines in 2026
<1%56%44%
3.48
3.5
Helga Sauza
76W–39L career · 19 lines in 2026
1%91%9%
3.32
3
Cristina da Costa
67W–92L career · 24 lines in 2026
8%91%1%
2.68
Jeanette Tan
39W–51L career · 10 lines in 2026
not enough data
Jennifer Woo
81W–101L career · 17 lines in 2026
not enough data
Lori Armendariz
52W–55L career · 27 lines in 2026
not enough data
Patricia Moye Holderman
66W–54L career · 20 lines in 2026
not enough data
Rose Rivera
25W–43L career · 11 lines in 2026
not enough data
Sonia Rangel
30W–68L career · 33 lines in 2026
not enough data
Stephanie Kwan
29W–43L career · 5 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.