Teams

Heathrow-Pan- Hunters

2025 ORANGESEMINOLE Mixed 40 & Over ESL-Fall · 7.0 Mixed 40 & Over ESL

14 players · average NTRP 3.50 / REGION_4

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 →
Schedule1 played
2024-11-17vs Red Bug-Luter/FaubertWon 21
W#1 DoublesSean Lu / Catherine Hwang vs Rayn Wu / Amy Morris6-2, 6-0
L#2 DoublesStella Liu / Romeo Bautista vs Joseph Parris / Katie Wu6-4, 4-6, 0-1
W#3 DoublesJun Pan / Donghui Zhang vs Stephen Vogelpohl / Wyetta Ford6-2, 6-0
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 standings for 7.0 Mixed 40 & Over ESL 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 3.35 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.

3.69
3.50
Luis Batista
published
3.50
Sean Lu
usually #1 Doubles 100% · published
3.38
Bing Tien
published 3.5
3.31
Donghui Zhang
usually #3 Doubles 100% · published
3.31
Catherine Hwang
usually #1 Doubles 100% · published 3.5
3.22
Ianthe Cocca
published
2.92
Zhiyi Zhou
published
Charlene Lane
published 3
Jun Pan
usually #3 Doubles 100% · published
Marvin Yee
published
Romeo Bautista
usually #2 Doubles 100% · published
Serena Jin
published
Stella Liu
usually #2 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.

Stella Liu + Bing Tien2352% gamesnot enough data
Luis Batista + Zhiyi Zhou3251% gamesnot enough data
Ianthe Cocca + Romeo Bautista0529% gamesnot enough data
Ashok Ramakrishnan + Stella Liu123 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
Ashok Ramakrishnan
5W–8L career · no lines in 2025
9%90%1%
3.69
Luis Batista
6W–5L career · no lines in 2025
49%51%<1%
3.50
Sean Lu
6W–10L career · 1 line in 2025
50%50%<1%
3.50
3.5
Bing Tien
10W–10L career · no lines in 2025
<1%80%20%
3.38
Donghui Zhang
15W–5L career · 1 line in 2025
1%90%8%
3.31
3.5
Catherine Hwang
4W–5L career · type S · 1 line in 2025
1%90%8%
3.31
Ianthe Cocca
5W–17L career · no lines in 2025
6%92%2%
3.22
Zhiyi Zhou
9W–8L career · no lines in 2025
<1%71%29%
2.92
3
Charlene Lane
1W–3L career · no lines in 2025
not enough data
Jun Pan
7W–14L career · 1 line in 2025
not enough data
Marvin Yee
0W–6L career · no lines in 2025
not enough data
Romeo Bautista
3W–10L career · 1 line in 2025
not enough data
Serena Jin
1W–3L career · no lines in 2025
not enough data
Stella Liu
18W–11L career · 1 line 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.