Teams

GEPTA/40&overMX/8.0/Woo/EPTC#1

SouthernNewMexico · 2025 USA MIXED 40 & OVER LEAGUE

15 players · average NTRP 3.90 / GEPTA

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Flight standings for 2025 USA MIXED 40 & OVER LEAGUE 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 3.66 estimated across 6 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.

4.39
Hope Perez
usually #2 Doubles 43%, also #1 Doubles 24% · published 4.5
3.89
Mike Caldarella
usually #2 Doubles 42%, also #1 Doubles 39% · published
3.70
Aaron Setliff
usually #2 Doubles 33%, also #2 Singles 25% · published 4
3.64
Ernestina Herrera
usually #3 Doubles 50%, also #1 Doubles 30% · published 4
3.21
Arvind Singhal
usually #3 Doubles 50%, also #2 Doubles 31% · published 3.5
3.15
EDMUND OSEI-WUSU
usually #1 Doubles 38%, also #2 Doubles 33% · published 3.5
Jeanette Tan
usually #3 Doubles 58%, also #2 Doubles 25% · published
Jennifer Woo
usually #2 Doubles 53%, also #1 Doubles 37% · published
Jesus Martinez
usually #2 Doubles 56%, also #3 Doubles 28% · published
Juan Herrera
usually #2 Doubles 54%, also #1 Doubles 23% · published
Lori DeLisser
usually #3 Doubles 55%, also #1 Doubles 35% · published
MarieJosee Lefebvre
usually #1 Doubles 37%, also #2 Doubles 32% · published
Nathan Brown
usually #3 Doubles 48%, also #2 Doubles 33% · published
Stephanie Kwan
usually #2 Doubles 53%, also #1 Doubles 27% · published
Steven Haynes
usually #2 Doubles 37%, also #1 Doubles 37% · 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.

Hope Perez + MarieJosee Lefebvre121150% games+2.4% vs expected
Jeanette Tan + MarieJosee Lefebvre141551% games+0.2% vs expected
Stephanie Kwan + Jennifer Woo101049% games−8.4% vs expected
EDMUND OSEI-WUSU + Arvind Singhal3258% gamesnot enough data
Jennifer Woo + Aaron Setliff2350% gamesnot enough data
Steven Haynes + Lori DeLisser224 matchesnot enough data
Ernestina Herrera + Lori DeLisser314 matchesnot enough data
Nathan Brown + Aaron Setliff044 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.

4.5
Hope Perez
43W–44L career · 21 lines in 2025
<1%81%19%
4.39
Mike Caldarella
41W–40L career · 33 lines in 2025
<1%79%21%
3.89
4
Aaron Setliff
14W–27L career · 11 lines in 2025
6%93%1%
3.70
4
Ernestina Herrera
12W–20L career · 10 lines in 2025
15%85%<1%
3.64
3.5
Arvind Singhal
57W–55L career · 32 lines in 2025
5%94%1%
3.21
3.5
EDMUND OSEI-WUSU
48W–85L career · 19 lines in 2025
13%87%<1%
3.15
Jeanette Tan
39W–51L career · 12 lines in 2025
not enough data
Jennifer Woo
81W–101L career · 19 lines in 2025
not enough data
Jesus Martinez
60W–33L career · 18 lines in 2025
not enough data
Juan Herrera
44W–46L career · 13 lines in 2025
not enough data
Lori DeLisser
94W–74L career · 20 lines in 2025
not enough data
MarieJosee Lefebvre
103W–76L career · 19 lines in 2025
not enough data
Nathan Brown
59W–32L career · 21 lines in 2025
not enough data
Stephanie Kwan
29W–43L career · 15 lines in 2025
not enough data
Steven Haynes
80W–58L career · 19 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.