Teams

SGV Underdogs Mixed-Bonilla-Diamond Bar HS/Su 10:00

2022 Mixed Doubles - 18 & Over San Gabriel Valley · SGV - 8.0 Mixed Division

13 players · average NTRP 3.95 / 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 - 8.0 Mixed Division 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 3.65 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.

4.06
Derek Fu
published 4
4.04
Alison Harma
published 4.5
3.95
Victor Nuguid
published 4
3.85
Andrew Mesdjian
published 4
3.79
Ted Nuguid
usually #2 Doubles 100% · published 4
Alan Gee
published 4
3.59
Ennie Gonzaga
usually #2 Doubles 50%, also #3 Doubles 50% · published 4
3.49
Aydee Martinez
usually #1 Doubles 100% · published 4
3.43
Yong Yoo
published
3.40
3.29
Gloria Nuguid
usually #1 Doubles 100% · published 3.5
Chinna Ponnaganti
published 3.5
3.25
Regina Cheung
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.

Gloria Nuguid + Victor Nuguid283348% games+5.6% vs expected
Ennie Gonzaga + Ted Nuguid92639% games−13.8% vs expected
Aydee Martinez + Ted Nuguid1534% games−14.2% vs expected
Aydee Martinez + Victor Nuguid314 matchesnot enough data
Victor Nuguid + Ennie Gonzaga303 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
Derek Fu
12W–4L career · no lines in 2022
<1%32%68%
4.06
4.5
Alison Harma
1W–6L career · no lines in 2022
39%61%<1%
4.04
4
Victor Nuguid
112W–94L career · no lines in 2022
<1%64%36%
3.95
4
Andrew Mesdjian
7W–5L career · no lines in 2022
<1%88%12%
3.85
4
Ted Nuguid
50W–79L career · 4 lines in 2022
1%93%6%
3.79
4
Alan Gee
1W–1L career · type S · no lines in 2022
not enough data
4
Ennie Gonzaga
112W–93L career · 6 lines in 2022
25%75%<1%
3.59
4
Aydee Martinez
81W–78L career · 2 lines in 2022
52%48%<1%
3.49
Yong Yoo
18W–10L career · no lines in 2022
<1%71%29%
3.43
Oscar Alberto Bonilla
7W–1L career · no lines in 2022
<1%78%22%
3.40
3.5
Gloria Nuguid
113W–98L career · 5 lines in 2022
1%93%5%
3.29
3.5
Chinna Ponnaganti
1W–4L career · no lines in 2022
not enough data
Regina Cheung
9W–12L career · no lines in 2022
3%95%3%
3.25

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.