Teams

SGV FC Spinners-Nichols-Flint Canyon/SU 12

2022 Mixed Doubles - 18 & Over San Gabriel Valley · SGV - 7.0 Mixed Division

20 players · average NTRP 3.67 / 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 - 7.0 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 3.50 estimated across 15 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.

4.03
Irina Abadzheva
usually #2 Doubles 50%, also #1 Doubles 33% · published 4
3.85
Dave Sparks
published 4
3.83
Susan Yu
published
3.81
3.79
Yukishi Yamamoto
published
3.70
Esther Hwang
published 4
3.69
Joanne Kim
published
3.56
Vladimir Abadzhev
published
3.35
Thomas Hegelund
published
3.34
Feiming Morgan
published 3.5
3.26
Antoinette Lessuk
usually #1 Doubles 100% · published 3.5
3.26
Helle Hegelund
published 3.5
3.22
Carla Denker
usually #1 Doubles 67%, also #2 Doubles 33% · published 3.5
2.90
Katherine Loevinger
published
2.84
David Loevinger
published 3
Matthew Hoffman
published
Michelle McMichael
published
Olivia Olivares
usually #2 Doubles 100% · published
Peter Nelson
published
Roger Duncan
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.

Irina Abadzheva + Vladimir Abadzhev4845% games−5.0% vs expected
Helle Hegelund + Thomas Hegelund1936% games−25.8% vs expected
Antoinette Lessuk + Matthew Hoffman2640% gamesnot enough data
Feiming Morgan + Peter Nelson2348% 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.

4
Irina Abadzheva
234W–146L career · 6 lines in 2022
<1%40%60%
4.03
4
Dave Sparks
26W–22L career · no lines in 2022
<1%87%13%
3.85
Susan Yu
20W–13L career · no lines in 2022
1%90%10%
3.83
4
Ferdinand Fontanilla
6W–2L career · no lines in 2022
1%92%7%
3.81
Yukishi Yamamoto
7W–10L career · no lines in 2022
1%94%5%
3.79
4
Esther Hwang
17W–8L career · no lines in 2022
6%93%1%
3.70
Joanne Kim
8W–16L career · no lines in 2022
8%91%1%
3.69
Vladimir Abadzhev
7W–14L career · no lines in 2022
31%69%<1%
3.56
Thomas Hegelund
5W–18L career · no lines in 2022
87%13%<1%
3.35
3.5
Feiming Morgan
6W–13L career · no lines in 2022
<1%88%11%
3.34
3.5
Antoinette Lessuk
164W–156L career · 1 line in 2022
2%94%3%
3.26
3.5
Helle Hegelund
8W–19L career · type A · no lines in 2022
2%95%3%
3.26
3.5
Carla Denker
158W–132L career · 3 lines in 2022
4%94%2%
3.22
Katherine Loevinger
2W–3L career · no lines in 2022
<1%78%22%
2.90
3
David Loevinger
6W–5L career · no lines in 2022
<1%88%12%
2.84
Matthew Hoffman
3W–5L career · no lines in 2022
not enough data
Michelle McMichael
0W–2L career · no lines in 2022
not enough data
Olivia Olivares
56W–55L career · 1 line in 2022
not enough data
Peter Nelson
5W–4L career · no lines in 2022
not enough data
Roger Duncan
0W–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.