Teams

SGV Top Guns - Tse - WN/SA 10

2022 Adult Division - 40& Over San Gabriel Valley · SGV - Men 3.5

12 players · average NTRP 3.00 / 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 SGV - Men 3.5 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 2.81 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.

3.34
Kumar Chatulani
published
3.10
Lansing Chew
published
3.01
Carlos Dinkel
published 3
2.95
Antonio Gonella
usually #2 Doubles 38%, also #1 Doubles 38% · published 3
2.87
Kasra Soufi
published
2.78
Gary Price
published 3
2.78
Sammy Tse
published
2.71
Edward Wong
published 3
2.56
Dan Schiffman
published 3
2.52
Don Woo
published 3
2.34
Simon Chow
published
Juan Mireles
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.

Dan Schiffman + Kasra Soufi3447% games−9.2% vs expected
Sammy Tse + Simon Chow0531% 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.

Kumar Chatulani
7W–2L career · no lines in 2022
<1%88%11%
3.34
Lansing Chew
4W–7L career · no lines in 2022
21%79%<1%
3.10
3
Carlos Dinkel
11W–6L career · no lines in 2022
<1%46%54%
3.01
3
Antonio Gonella
23W–37L career · 8 lines in 2022
<1%66%34%
2.95
Kasra Soufi
13W–17L career · no lines in 2022
<1%83%17%
2.87
3
Gary Price
10W–5L career · no lines in 2022
2%94%5%
2.78
Sammy Tse
16W–29L career · no lines in 2022
2%94%4%
2.78
3
Edward Wong
7W–6L career · no lines in 2022
5%93%1%
2.71
3
Dan Schiffman
10W–26L career · no lines in 2022
32%67%<1%
2.56
3
Don Woo
5W–4L career · no lines in 2022
44%56%<1%
2.52
Simon Chow
4W–20L career · no lines in 2022
89%11%<1%
2.34
Juan Mireles
4W–11L 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.