Teams

MSIL/Wang/X18&Over7.0

2025 MSIL Mixed 18 & Over - MSIL West League · West MSIL Mixed 18 & Over 7.0

16 players · average NTRP 3.56 / MID-SOUTH ILLINOIS

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 →
Schedule6 played
L#2 DoublesNoel Castro / JOOYEN KIM vs Erik Siembab / Ashley Dallapiazza2-6, 2-6
W#3 DoublesPatrick Hammie / Minsun Kim vs Joseph McCarron / Paige McNamara6-2, 6-3
W#1 DoublesNoel Castro / Karolyn Smith vs Robert Vanhootegem / Sally Boland6-3, 6-1
W#2 DoublesPatrick Hammie / Minsun Kim vs Craig Conway / Marla Golden6-1, 6-3
W#1 DoublesAngad Mehta / Minsun Kim vs Chris Ehrlich / Amber Ehrlich6-3, 6-1
L#2 DoublesBen Lee / Lisa Ainsworth vs Luis Felipe Hernandez / Marla Golden3-6, 4-6
W#3 DoublesSung Min Moon / Teri Scaggs vs Craig Conway / Sally Boland7-5, 6-2
W#1 DoublesSung Min Moon / Teri Scaggs vs Annaliese McDermott / Nicholas Troehler6-3, 2-6, 1-0
W#2 DoublesAngad Mehta / Lisa Ainsworth vs Paige McNamara / Joseph McCarron6-4, 6-4
W#3 DoublesBen Lee / Minsun Kim vs Abby Delgado / Ranjit Gadicherla6-1, 6-2
W#1 DoublesLijian Zhang / Su A Lee vs Sean Miller / Janet Hogan6-0, 6-1
W#2 DoublesChris Sarol / Kym Man vs John Delanois / Cynthia Ottemann6-4, 1-6, 1-0
W#3 DoublesKai Wang / Kyo Nakanishi vs Brett Henneberg / Abby Delgado6-1, 6-3
W#1 DoublesChris Sarol / Kym Man vs William Ehrlich / Colleen Larry6-3, 6-4
L#2 DoublesKai Wang / Kyo Nakanishi vs Luis Felipe Hernandez / Isabella Griffiths3-6, 2-6
W#3 DoublesLijian Zhang / Su A Lee vs Mihai Mihailescu / Sally Boland6-1, 3-6, 1-0
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 · West MSIL Mixed 18 & Over 7.0
TeamWLInd. WInd. LSets lostGames lost
1MSIL/Wang/X18&Over7.06015310117
2MSIL Mixed 18&O 7.0 Vanhootegem-Decatur2471122172
3MSIL Mixed 18&O 7.0 McNamara-Bloomington1551327174

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 3.39 estimated across 14 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.

3.89
Teri Scaggs
usually #2 Doubles 50%, also #1 Doubles 38% · published 4
3.88
Chris Sarol
usually #3 Doubles 50%, also #1 Doubles 30% · published 4
3.70
Noel Castro
usually #1 Doubles 75%, also #2 Doubles 25% · published
3.56
Angad Mehta
usually #1 Doubles 33%, also #3 Doubles 33% · published 4
3.49
Kyo Nakanishi
usually #3 Doubles 50%, also #2 Doubles 50% · published
3.43
Su A Lee
usually #1 Doubles 50%, also #3 Doubles 50% · published
3.38
Ben Lee
usually #2 Doubles 50%, also #3 Doubles 50% · published 3.5
3.34
Lijian Zhang
usually #3 Doubles 50%, also #1 Doubles 50% · published 3.5
3.33
Patrick Hammie
usually #3 Doubles 50%, also #2 Doubles 50% · published 3.5
3.19
Lisa Ainsworth
usually #2 Doubles 100% · published
3.17
Kym Man
usually #2 Doubles 50%, also #1 Doubles 50% · published
3.06
Sung Min Moon
usually #3 Doubles 50%, also #1 Doubles 50% · published
3.02
JOOYEN KIM
usually #2 Doubles 50%, also #3 Doubles 50% · published 3
2.98
Karolyn Smith
usually #1 Doubles 100% · published 3
Kai Wang
published
Minsun Kim
usually #3 Doubles 44%, also #2 Doubles 33% · 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.

Minsun Kim + Chris Sarol18661% games+14.6% vs expected
JOOYEN KIM + Lijian Zhang21367% games+1.0% vs expected
JOOYEN KIM + Noel Castro4446% games−14.2% vs expected
Teri Scaggs + Sung Min Moon8064% gamesnot enough data
Su A Lee + Lijian Zhang6258% gamesnot enough data
Minsun Kim + Noel Castro2342% gamesnot enough data
JOOYEN KIM + Kai Wang2355% gamesnot enough data
Minsun Kim + Patrick Hammie404 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
Teri Scaggs
129W–53L career · 8 lines in 2025
<1%78%22%
3.89
4
Chris Sarol
109W–28L career · 10 lines in 2025
<1%81%19%
3.88
Noel Castro
65W–41L career · 4 lines in 2025
7%91%2%
3.70
4
Angad Mehta
53W–18L career · 3 lines in 2025
33%67%<1%
3.56
Kyo Nakanishi
20W–4L career · 2 lines in 2025
<1%53%47%
3.49
Su A Lee
32W–14L career · 2 lines in 2025
<1%70%30%
3.43
3.5
Ben Lee
7W–4L career · 2 lines in 2025
<1%81%19%
3.38
3.5
Lijian Zhang
112W–59L career · 2 lines in 2025
1%86%13%
3.34
3.5
Patrick Hammie
37W–38L career · 2 lines in 2025
1%87%12%
3.33
Lisa Ainsworth
11W–10L career · 2 lines in 2025
8%90%1%
3.19
Kym Man
27W–14L career · 2 lines in 2025
<1%12%88%
3.17
Sung Min Moon
41W–21L career · 2 lines in 2025
<1%35%65%
3.06
3
JOOYEN KIM
115W–64L career · 2 lines in 2025
<1%45%55%
3.02
3
Karolyn Smith
79W–65L career · 2 lines in 2025
<1%56%43%
2.98
Kai Wang
35W–23L career · no lines in 2025
not enough data
Minsun Kim
112W–21L career · 9 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.