Teams

BAY TREES PK 40MX7.0A

2025 MIXED 40&Over · 40&Over MX7.0

23 players · average NTRP 3.43 / NO. CALIFORNIA

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 →

Flight standings for 40&Over MX7.0 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 3.34 estimated across 19 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.

David Pawid
usually #1 Doubles 100% · published 4
3.71
Lual Lualhati
usually #3 Doubles 67%, also #2 Doubles 33% · published
3.70
Janie McCauley
usually #3 Doubles 100% · published
3.64
Jeffrey Cannon
usually #1 Doubles 100% · published
3.62
Tuesdai Powers
published
3.58
Yemia Hashimoto
published
3.53
Chen Zhang
published 3.5
3.46
Steven Fralick
published
3.46
Sathyanand Balan
published
3.38
Minh Cannon
usually #2 Doubles 67%, also #3 Doubles 33% · published
3.37
Nga Gross
published
3.28
Julieta Leong
published
Amer Malik
published 3.5
3.21
Rama ERIGINDINDLA
usually #3 Doubles 50%, also #2 Doubles 25% · published 3.5
3.20
Harvey Sue
usually #2 Doubles 100% · published 3.5
3.16
Kwok Yin Chan
published
3.13
JoAnn Pawid
published
3.09
Allie Fralick
published 3
3.06
Anna Bowe
published 3
3.03
S George Wong
published
2.91
Linda Duchscherer
usually #1 Doubles 100% · published
Joel Wanek
published
Nick Halatsis
usually #2 Doubles 33%, also #1 Doubles 33% · published
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
David Pawid
0W–1L career · 1 line in 2025
not enough data
Lual Lualhati
28W–15L career · 3 lines in 2025
6%93%1%
3.71
Janie McCauley
18W–16L career · 1 line in 2025
6%93%1%
3.70
Jeffrey Cannon
19W–22L career · 1 line in 2025
15%85%<1%
3.64
Tuesdai Powers
24W–30L career · no lines in 2025
19%81%<1%
3.62
Yemia Hashimoto
35W–35L career · no lines in 2025
<1%26%74%
3.58
3.5
Chen Zhang
11W–10L career · no lines in 2025
<1%42%58%
3.53
Steven Fralick
6W–5L career · no lines in 2025
<1%62%38%
3.46
Sathyanand Balan
0W–4L career · no lines in 2025
63%37%<1%
3.46
Minh Cannon
61W–38L career · 3 lines in 2025
<1%81%19%
3.38
Nga Gross
17W–24L career · no lines in 2025
<1%84%16%
3.37
Julieta Leong
8W–9L career · no lines in 2025
2%94%4%
3.28
3.5
Amer Malik
0W–1L career · no lines in 2025
not enough data
3.5
Rama ERIGINDINDLA
71W–52L career · 4 lines in 2025
5%94%1%
3.21
3.5
Harvey Sue
10W–12L career · 2 lines in 2025
6%93%1%
3.20
Kwok Yin Chan
11W–8L career · no lines in 2025
11%89%<1%
3.16
JoAnn Pawid
12W–5L career · no lines in 2025
<1%16%84%
3.13
3
Allie Fralick
4W–4L career · no lines in 2025
<1%25%75%
3.09
3
Anna Bowe
17W–8L career · no lines in 2025
<1%32%68%
3.06
S George Wong
11W–10L career · no lines in 2025
<1%41%59%
3.03
Linda Duchscherer
22W–16L career · 1 line in 2025
<1%75%24%
2.91
Joel Wanek
0W–1L career · no lines in 2025
not enough data
Nick Halatsis
13W–22L career · 3 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.