Teams

WI Mid Tri Mixed Doubles MALT Isensee

2025 WI Other · WI Mid Tri Mixed Doubles

11 players · average NTRP 4.00 / WISCONSIN

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Schedule2 played
2025-09-16Won 10
W#1 DoublesJustin Yee / Kayla O'Neill vs Brian Kosobucki / Sydney Verbauwhede6-4, 7-5
L#1 DoublesJustin Yee / Kayla O'Neill vs Jacob Rodgers / Michelle Tallentyre3-6, 3-6
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 standings3 teams · WI Mid Tri Mixed Doubles
TeamWLInd. WInd. LSets lostGames lost
1WI Mid Tri Mixed Doubles MALT Kosobucki60144990
2WI Mid Tri Mixed Doubles MALT Isensee135716121
3WI Mid Tri Mixed Doubles MALT Arreazola0421021140

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 3.87 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.

4.47
Justin Yee
usually #1 Doubles 63%, also #2 Doubles 38% · published
3.96
Megan Prahl
usually #1 Doubles 44%, also #2 Doubles 44% · published
3.96
Enes Akyuz
usually #1 Singles 62%, also #1 Doubles 15% · published
3.86
Pallavi Tiwari
usually #1 Doubles 53%, also #3 Doubles 27% · published 4
3.85
Erik Dustrude
usually #1 Singles 36%, also #1 Doubles 29% · published
3.52
Shaleen Deep
usually #3 Doubles 40%, also #2 Doubles 33% · published
3.44
Chris Isensee
usually #2 Singles 67%, also #3 Doubles 11% · published 4
Emma Verret
usually #3 Doubles 50%, also #1 Doubles 33% · published
Kayla O'Neill
usually #1 Doubles 100% · published
Roxie Anderson
usually #1 Doubles 100% · published
Xiaotong Wang
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.

Pallavi Tiwari + Shaleen Deep2446% games−1.6% vs expected
Chris Isensee + Erik Dustrude4254% gamesnot enough data
Pallavi Tiwari + Erik Dustrude314 matchesnot enough data
Megan Prahl + Erik Dustrude033 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.

Justin Yee
100W–50L career · 8 lines in 2025
<1%58%42%
4.47
Megan Prahl
100W–45L career · 16 lines in 2025
<1%62%38%
3.96
Enes Akyuz
103W–59L career · 12 lines in 2025
<1%62%38%
3.96
4
Pallavi Tiwari
96W–58L career · 15 lines in 2025
<1%83%16%
3.86
Erik Dustrude
57W–55L career · 14 lines in 2025
1%85%14%
3.85
Shaleen Deep
61W–24L career · 15 lines in 2025
<1%43%57%
3.52
4
Chris Isensee
51W–96L career · type A · 9 lines in 2025
67%33%<1%
3.44
Emma Verret
7W–17L career · 6 lines in 2025
not enough data
Kayla O'Neill
17W–5L career · 2 lines in 2025
not enough data
Roxie Anderson
34W–10L career · 3 lines in 2025
not enough data
Xiaotong Wang
14W–6L 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.