Teams

SD LT SDTRC/ Dube

2026 Mixed Doubles Tri-Level Fall - SD · SD (8.0

13 players · average NTRP 3.71 / SAN DIEGO

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 standings7 teams · SD (8.0
TeamWLInd. WInd. LSets lostGames lost
1SD LT SDTRC/ Adams000000
2SD LT ECCTA/ Rozo- Runde000000
3SD LT Balboa TC/ Tan000000
4SD LT Balboa M&M's/ Afifi000000
5SD LT Peninsula TC/ Miller000000
6SD LT Mtn View/ Cortez000000
7SD LT SDTRC/ Dube000000

Ordered by team wins, then losses, then sets lost — the order USTA uses to seed a flight. Individual wins are lines, not ties.

See the full flight, with every team’s record

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 3.34 estimated across 10 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.

3.84
Yusuf Yazici
published 4
3.83
Tim Pillow
published 4
3.75
Soledad Ramirez
published 4
3.52
Colin Chang
published 4
3.29
Kelly Ann Tran
published
3.28
Randall Bolelli
published 3.5
3.14
Matt Whitmire
published
3.07
Donna Dube
published 3.5
2.96
Millie Touch
published
2.75
Lisa Bolelli
published 3
Jeffrey Strong
published
Natalie Whitmire
published
Rebecca Riley
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.

Lisa Bolelli + Randall Bolelli52042% games+4.2% vs expected
Soledad Ramirez + Yusuf Yazici123 matchesnot enough data
Rebecca Riley + Randall Bolelli123 matchesnot enough data
Randall Bolelli + Donna Dube213 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
Yusuf Yazici
31W–18L career · no lines in 2026
<1%88%11%
3.84
4
Tim Pillow
50W–69L career · no lines in 2026
1%90%10%
3.83
4
Soledad Ramirez
114W–102L career · no lines in 2026
3%95%3%
3.75
4
Colin Chang
1W–11L career · no lines in 2026
43%57%<1%
3.52
Kelly Ann Tran
2W–2L career · no lines in 2026
1%94%5%
3.29
3.5
Randall Bolelli
45W–56L career · no lines in 2026
2%94%5%
3.28
Matt Whitmire
6W–9L career · no lines in 2026
15%85%<1%
3.14
3.5
Donna Dube
118W–125L career · no lines in 2026
30%70%<1%
3.07
Millie Touch
0W–7L career · no lines in 2026
<1%63%37%
2.96
3
Lisa Bolelli
61W–80L career · no lines in 2026
2%95%3%
2.75
Jeffrey Strong
2W–5L career · no lines in 2026
not enough data
Natalie Whitmire
0W–1L career · no lines in 2026
not enough data
Rebecca Riley
7W–10L career · no lines in 2026
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.