Teams

PINOLE PK 40MX7.0A

2022 MIXED 40&Over · 40&Over MX7.0

14 players · average NTRP 3.61 / 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 3.39 estimated across 12 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.

3.71
Robert Duong
published
3.70
Maggie Ho
published
3.67
Cliff Liang
published 4
3.54
Kimberly Caison
published
3.46
Gary Hazard
published 3.5
3.44
Alexander Michael
published 3.5
3.44
Chamane Ifland
usually #2 Doubles 40%, also #1 Doubles 33% · published 4
3.43
Gina Chen
published 4
3.32
Anna Le
published 3.5
3.29
Albert Chu
published 3.5
Ed Wong
published 3.5
2.91
Jan Wilkins
published
2.77
Anita Lifson
published 3
Simon Kwan
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.

Robert Duong
31W–41L career · no lines in 2022
5%93%1%
3.71
Maggie Ho
14W–8L career · no lines in 2022
6%93%1%
3.70
4
Cliff Liang
8W–0L career · no lines in 2022
9%90%1%
3.67
Kimberly Caison
7W–3L career · no lines in 2022
<1%37%63%
3.54
3.5
Gary Hazard
3W–1L career · no lines in 2022
<1%63%37%
3.46
3.5
Alexander Michael
19W–18L career · no lines in 2022
<1%67%32%
3.44
4
Chamane Ifland
107W–54L career · 15 lines in 2022
68%32%<1%
3.44
4
Gina Chen
27W–19L career · no lines in 2022
69%31%<1%
3.43
3.5
Anna Le
11W–4L career · no lines in 2022
1%91%9%
3.32
3.5
Albert Chu
7W–5L career · no lines in 2022
1%93%6%
3.29
3.5
Ed Wong
0W–1L career · no lines in 2022
not enough data
Jan Wilkins
1W–9L career · no lines in 2022
76%24%<1%
2.91
3
Anita Lifson
6W–1L career · type M · no lines in 2022
2%94%4%
2.77
Simon Kwan
10W–1L 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.