Teams

STONEBRAE 40MX6.0A

2022 MIXED 40&Over · 40&Over MX6.0

17 players · average NTRP 3.40 / 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 3.11 estimated across 14 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.

3.64
Jeffrey Cannon
published
3.61
Kara Crowe
published
3.46
Jazelle Nono
published
3.38
Minh Cannon
published
Edward Tang
published 3.5
3.21
Tinara Choing
published
3.13
Oliver Nono
published
3.09
Hong Choing
published 3.5
3.04
Divya Bala
published 3.5
2.96
Lia Tjandra
published
2.92
Jean Kondo
published
2.87
Grace Fan
published 3.5
2.78
2.75
Trisha Shah
published
2.70
Femi Olujide
published 3
Mark Burdelle
published
Paris Greenwood
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.

Tinara Choing + Hong Choing1546% games−0.5% vs expected
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.

Jeffrey Cannon
19W–22L career · no lines in 2022
15%85%<1%
3.64
Kara Crowe
5W–15L career · no lines in 2022
20%80%<1%
3.61
Jazelle Nono
23W–9L career · no lines in 2022
<1%62%38%
3.46
Minh Cannon
61W–38L career · no lines in 2022
<1%81%19%
3.38
3.5
Edward Tang
1W–1L career · no lines in 2022
not enough data
Tinara Choing
1W–9L career · no lines in 2022
5%93%1%
3.21
Oliver Nono
19W–20L career · no lines in 2022
<1%16%84%
3.13
3.5
Hong Choing
6W–8L career · no lines in 2022
25%75%<1%
3.09
3.5
Divya Bala
8W–22L career · no lines in 2022
39%61%<1%
3.04
Lia Tjandra
6W–3L career · no lines in 2022
<1%61%39%
2.96
Jean Kondo
17W–19L career · no lines in 2022
<1%73%27%
2.92
3.5
Grace Fan
2W–17L career · no lines in 2022
83%17%<1%
2.87
Sophie de Saint Pierre
9W–12L career · no lines in 2022
2%94%4%
2.78
Trisha Shah
2W–4L career · no lines in 2022
3%95%3%
2.75
3
Femi Olujide
3W–4L career · no lines in 2022
6%93%1%
2.70
Mark Burdelle
4W–10L career · no lines in 2022
not enough data
Paris Greenwood
1W–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.