Teams

WSC-Wu

2026 Coed 18-39 · 4.5 Coed

9 players · average NTRP 4.29 / NORTHWEST WASHINGTON

View scouting list →
Schedule6 played
2026-03-08vs AYTC-Dinglers-TruongLost 13
L#1 Female DoublesDan Su / Margaux Steele vs Raveena Patil / Grace Bethards3-6
W#1 Female SinglesMargaux Steele vs Raveena Patil6-5
L#1 Male DoublesLinsen Wu / Evan Liu vs Alexander Calpagiu / Oscar Cruz2-6
L#1 Male SinglesEvan Liu vs Oscar Cruz0-6
W#1 Female DoublesLiz Perlman / Mina Park vs Kate Beardslee / Amarlin Distelhorst6-5
L#1 Female SinglesLiz Perlman vs Kate Beardslee2-6
L#1 Male DoublesTimothy Wu / Linsen Wu vs Jake Murray / Youssef Shalaby5-6
L#1 Male SinglesLinsen Wu vs Jake Murray2-6
L#1 Female SinglesDan Su vs Nicole Bouche2-6
L#1 Male DoublesTimothy Wu / George Tam vs Pinoe Chu / Hiromichi Yamamoto0-6
L#1 Male SinglesGeorge Tam vs Aditya Iyer3-6
2026-01-24vs TCSP-Haffyin Fun Yet? YinSplit 22
W#1 Female DoublesMargaux Steele / Jessica Wang vs Megan Huffman / Shanifer Seit6-1
W#1 Female SinglesMargaux Steele vs Rina Chen6-1
L#1 Male DoublesTimothy Wu / Evan Liu vs Bruno Diaz Torres / Evan Pan1-6
L#1 Male SinglesTimothy Wu vs Bruno Diaz Torres0-6
2026-01-18vs TCSP-Haffyin Fun Yet? YinLost 13
L#1 Female DoublesDan Su / Liz Perlman vs Qiya Yin / Sydney Bloch4-6
W#1 Female SinglesLiz Perlman vs Qiya Yin6-3
L#1 Male DoublesGeorge Tam / Evan Liu vs Djelli Berisha / OLIVER LEI0-6
L#1 Male SinglesEvan Liu vs Djelli Berisha5-6
2026-01-16vs AYTC-Dinglers-TruongLost 13
L#1 Female DoublesJessica Wang / Liz Perlman vs Raveena Patil / Grace Bethards5-6
W#1 Female SinglesLiz Perlman vs Raveena Patil6-1
L#1 Male DoublesLinsen Wu / George Tam vs Oscar Cruz / Lucas Gorretta2-6
L#1 Male SinglesLinsen Wu vs Alexander Calpagiu2-6
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 standings for 4.5 Coed 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 3.91 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.

4.34
Margaux Steele
usually #1 Female Singles 100% · published 4.5
4.16
Liz Perlman
usually #1 Female Singles 100% · published 4.5
4.12
Dan Su
usually #1 Female Doubles 67%, also #1 Female Singles 33% · published 4.5
3.93
Evan Liu
usually #1 Male Singles 67%, also #1 Male Doubles 33% · published 4
3.89
Linsen Wu
usually #1 Male Singles 50%, also #1 Male Doubles 50% · published 4
3.79
Jessica Wang
usually #1 Female Doubles 100% · published 4.5
3.64
Mina Park
usually #1 Female Doubles 60%, also #1 Female Singles 40% · published 4
3.45
Timothy Wu
usually #1 Male Doubles 67%, also #1 Male Singles 33% · published
George Tam
usually #1 Male Doubles 67%, also #1 Male Singles 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.

Timothy Wu + Linsen Wu0719% games−10.2% vs expected
George Tam + Timothy Wu0519% gamesnot enough data
George Tam + Jessica Wang134 matchesnot enough data
Linsen Wu + Jessica Wang314 matchesnot enough data
Dan Su + Jessica Wang314 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
Margaux Steele
30W–23L career · 2 lines in 2026
<1%89%10%
4.34
4.5
Liz Perlman
18W–13L career · 3 lines in 2026
11%88%<1%
4.16
4.5
Dan Su
29W–17L career · 3 lines in 2026
19%81%<1%
4.12
4
Evan Liu
23W–28L career · 3 lines in 2026
<1%71%29%
3.93
4
Linsen Wu
70W–76L career · 8 lines in 2026
<1%80%19%
3.89
4.5
Jessica Wang
45W–53L career · 2 lines in 2026
95%5%<1%
3.79
4
Mina Park
70W–48L career · 5 lines in 2026
14%85%<1%
3.64
Timothy Wu
3W–28L career · 3 lines in 2026
64%36%<1%
3.45
George Tam
6W–17L career · 3 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.