Teams

SFV - Burbank Breaking Bad

2022 SCTA Tri-Level 18+ SFV · SFV - Men's 3.0-4.0

13 players · average NTRP 3.64 / SO.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 SFV - Men's 3.0-4.0 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 3.41 estimated across 11 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.

3.85
MacLyn McRae
usually #1 Doubles 100% · published 4
3.72
Won Cho
published
3.65
Stephen Kim
published
3.61
Edmond Avedisian
usually #1 Doubles 100% · published 4
3.42
Kevin Rodriguez
published
3.40
Aldo Angrisani
usually #2 Doubles 67%, also #1 Doubles 33% · published 3.5
3.27
Paul Ketrick
published
3.27
Glen Chester
published 3.5
3.22
Bruce Lilly
published 3.5
3.11
Gonzalo Mendez
published 3.5
3.06
Tim SCHUMACHER
published
Michael Pak
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.

Edmond Avedisian + MacLyn McRae5459% gamesnot enough data
Paul Ketrick + Gonzalo Mendez314 matchesnot enough data
Paul Ketrick + Glen Chester224 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
MacLyn McRae
94W–50L career · 5 lines in 2022
<1%88%12%
3.85
Won Cho
13W–14L career · no lines in 2022
4%94%2%
3.72
Stephen Kim
11W–18L career · no lines in 2022
13%87%<1%
3.65
4
Edmond Avedisian
104W–117L career · 5 lines in 2022
21%79%<1%
3.61
Kevin Rodriguez
30W–13L career · no lines in 2022
<1%73%27%
3.42
3.5
Aldo Angrisani
93W–87L career · 3 lines in 2022
<1%78%22%
3.40
Paul Ketrick
9W–12L career · no lines in 2022
2%94%4%
3.27
3.5
Glen Chester
5W–12L career · no lines in 2022
2%94%4%
3.27
3.5
Daniel Peterson-Beliakoff
0W–2L career · no lines in 2022
not enough data
3.5
Bruce Lilly
7W–6L career · no lines in 2022
4%94%2%
3.22
3.5
Gonzalo Mendez
9W–7L career · no lines in 2022
21%79%<1%
3.11
Tim SCHUMACHER
1W–5L career · no lines in 2022
34%66%<1%
3.06
Michael Pak
2W–3L 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.