Teams

BAY TREES PK 40MX6.0A

2022 MIXED 40&Over · 40&Over MX6.0

17 players · average NTRP 3.10 / 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 MX6.0 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 2.85 estimated across 13 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.

3.62
Tuesdai Powers
published
3.13
Gary Soto
published 3.5
3.00
Bob Koury
published 3
2.97
Kasey Chung
published
2.89
Maria Debenedetti
published
2.87
Olga Sokolov
published
2.84
Penny Lane
published
2.73
Shiow-Rong Lin
published
2.72
2.61
LyLy Kim
published
2.61
2.57
Ignatius Chan
published 3
2.48
Olivia Mattox
published
Manohar S Sohal
published
Nick Halatsis
published
Scott Yee
published
Walton Woo
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.

Maria Debenedetti + Bob Koury4161% gamesnot 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.

Tuesdai Powers
24W–30L career · no lines in 2022
19%81%<1%
3.62
3.5
Gary Soto
10W–6L career · no lines in 2022
15%85%<1%
3.13
3
Bob Koury
47W–20L career · type A · no lines in 2022
<1%50%50%
3.00
Kasey Chung
34W–12L career · no lines in 2022
<1%58%42%
2.97
Maria Debenedetti
29W–10L career · no lines in 2022
<1%80%19%
2.89
Olga Sokolov
28W–11L career · no lines in 2022
<1%84%16%
2.87
Penny Lane
21W–14L career · no lines in 2022
0%<1%>99%
2.84
Shiow-Rong Lin
5W–4L career · no lines in 2022
0%4%96%
2.73
3
Elaine Hackenkamp
3W–5L career · no lines in 2022
4%94%2%
2.72
LyLy Kim
24W–24L career · no lines in 2022
0%20%80%
2.61
3
Christopher Pagel
6W–8L career · no lines in 2022
20%80%<1%
2.61
3
Ignatius Chan
10W–10L career · no lines in 2022
29%71%<1%
2.57
Olivia Mattox
14W–22L career · no lines in 2022
0%58%42%
2.48
Manohar S Sohal
8W–9L career · no lines in 2022
not enough data
Nick Halatsis
13W–22L career · no lines in 2022
not enough data
Scott Yee
3W–0L career · no lines in 2022
not enough data
Walton Woo
0W–2L career · no 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.