Teams

Haiying-3.0-W-JXN

2026 Team Singles Tournament-PB · 3.0 W

8 players · average NTRP 3.25 / MISSISSIPPI

View scouting list →
Schedule4 played
2026-03-01vs Upshaw-3.0W-SWSplit 11
W#1 SinglesLifang Yan vs Bonita Upshaw6-2, 6-1
L#2 SinglesErica Scarbrough vs Kay Ketchings6-2, 6-7, 0-1
2026-03-01vs Hamrick-3.0W-DeltaWon 30
W#1 SinglesHaiying Anne Chen vs Mikki Respess6-0, 6-1
W#2 SinglesMarianna Redd vs Allison Brady6-1, 6-2
W#3 SinglesLI Zhou vs Haley Hamrick6-1, 6-0
2026-02-28vs Toups-3.0W-PBWon 21
W#1 SinglesAlexis Crews vs Sarah Bolton6-0, 6-2
W#2 SinglesMaggie Wei vs Candace Baye6-0, 6-1
L#3 SinglesAlyssa Taylor vs Ashley Vance4-6, 2-6
2026-02-28vs Matthews-3.0W-GCWon 21
L#1 SinglesHaiying Anne Chen vs Gracie Weatherly5-7, 4-6
W#2 SinglesAlexis Crews vs Julie Pace6-0, 6-1
W#3 SinglesMaggie Wei vs Brianna Beesley6-3, 6-3
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 standings5 teams · 3.0 W
TeamWLInd. WInd. LSets lostGames lost
1Haiying-3.0-W-JXN4093653
2Matthews-3.0W-GC3184980
3Toups-3.0W-PB227511105
4Hamrick-3.0W-Delta133920132
5Upshaw-3.0W-SW043921137

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 2.75 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.

3.10
Alexis Crews
usually #1 Singles 50%, also #2 Singles 50% · published 3.5
3.06
Maggie Wei
usually #2 Singles 50%, also #3 Singles 50% · published
2.91
Haiying Anne Chen
usually #1 Singles 100% · published
2.87
LI Zhou
usually #3 Singles 100% · published
2.59
Marianna Redd
usually #2 Singles 100% · published
2.56
Erica Scarbrough
usually #2 Singles 100% · published
2.48
Alyssa Taylor
usually #3 Singles 100% · published 3
2.40
Lifang Yan
usually #1 Singles 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.

Marianna Redd + Erica Scarbrough3248% games+0.8% vs expected
Haiying Anne Chen + Lifang Yan134 matchesnot enough data
Haiying Anne Chen + LI Zhou123 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.

3.5
Alexis Crews
15W–3L career · type D · 2 lines in 2026
24%76%<1%
3.10
Maggie Wei
21W–11L career · 2 lines in 2026
<1%35%65%
3.06
Haiying Anne Chen
23W–20L career · 2 lines in 2026
0%<1%>99%
2.91
LI Zhou
36W–22L career · 1 line in 2026
<1%82%18%
2.87
Marianna Redd
6W–6L career · 1 line in 2026
0%25%75%
2.59
Erica Scarbrough
9W–6L career · 1 line in 2026
0%33%67%
2.56
3
Alyssa Taylor
14W–15L career · type A · 1 line in 2026
55%45%<1%
2.48
Lifang Yan
15W–18L career · 1 line in 2026
0%76%24%
2.40

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.