Teams

BSF:MX Version 2.0:Song

2021 NCT Tri Level Women · 4.0 Women

3 players · average NTRP / NORTHERN CONNECTICUT

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 →
Schedule11 played
2021-11-24vs MRC:Zoldy:ZoldyWon 10
W#1 DoublesXianyuan Song / Maya BarLev vs Jackie Zoldy / Julie Mooney1-6, 6-3, 1-0
2021-11-23vs FV:Level Up:King/GoodwinLost 01
L#1 DoublesXianyuan Song / Maya BarLev vs Cari Anne Goodwin / Shea Kinney3-6, 2-6
2021-11-22vs FV:Queens of the court:SansoneWon 10
W#1 DoublesXianyuan Song / Maya BarLev vs Laurie Sansone / Esther Aronson6-3, 3-1
2021-11-08vs SIMS:Servivors:LeeWon 10
W#1 DoublesMing Yi / Maya BarLev vs Carolyn McGarr-Lee / Susan Emhoff6-0, 6-3
2021-11-06vs FV:Triba/BowersWon 10
W#1 DoublesMing Yi / Xianyuan Song vs Melanie Bowers / Kristen Triba5-7, 6-2, 1-0
2021-10-21vs BSF:DiBaccoWon 10
W#1 DoublesMing Yi / Xianyuan Song vs Jennifer Murnane / Leigh Bryson4-6, 6-2, 1-0
2021-10-20vs EHTC:Netminders:ParekhLost 01
L#1 DoublesXianyuan Song / Ming Yi vs Wendy Federer / Teri Parekh6-1, 1-6, 0-1
L#1 DoublesXianyuan Song / Ming Yi vs Katharine Miller / Stacey Weinstein4-6, 3-6
W#1 DoublesMing Yi / Maya BarLev vs Stacy Collins / Elizabeth Kaplan7-6, 5-6, 1-0
2021-10-07vs MRC:Luv wins:PalanzoWon 10
W#1 DoublesXianyuan Song / Maya BarLev vs Michele Palanzo / Audra Edele2-6, 6-4, 1-0
2021-09-19vs GTC:Not My Fault:Eller/McAuliffLost 01
L#1 DoublesXianyuan Song / Ming Yi vs Karen Eller / Suzanne Mc Auliffe7-5, 2-6, 0-1
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 standings12 teams · 4.0 Women
TeamWLInd. WInd. LSets lostGames lost
1MRC:Zoldy:Zoldy9292886
2FV:Level Up:King/Goodwin74741093
3BSF:MX Version 2.0:Song74741399
4MRC:Luv wins:Palanzo6464980
5GTC:Double Trouble:Weinstein/Miller65651188
6EHTC:Netminders:Parekh65651199
7SIMS:All the Singles Ladies:Kaplan/Collins656515116
8FV:Queens of the court:Sansone565614108
9SIMS:Servivors:Lee464614100
10FV:Triba/Bowers383817111
11BSF:DiBacco383817118
12GTC:Not My Fault:Eller/McAuliff383819121

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 3.92 estimated across 2 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.

3.95
Xianyuan Song
usually #1 Doubles 100% · published
3.89
Ming Yi
published
Maya BarLev
usually #1 Doubles 100% · 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.

Xianyuan Song + Maya BarLev314 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.

Xianyuan Song
113W–75L career · 9 lines in 2022
65%35%<1%
3.95
Ming Yi
16W–7L career · no lines in 2022
<1%80%20%
3.89
Maya BarLev
14W–5L career · 6 lines in 2022
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.