Teams

SD 4.0 Mountain View/ Killeen

2022 So Cal Fall Doubles SD · SDNC WE

11 players · average NTRP 3.95 / 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 standings for SDNC WE 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 3.55 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.

4.09
Junko Toda
published 4.5
Chigusa Okubo
published 4
3.69
Emi Kanayama
published 4
3.60
Jennifer Kries
published 4
3.60
Julie Wunderly
published 4
3.58
Veronica Ruffo
published 4
3.57
Joan Yngson
published
3.50
Haruko Vajda
published 4
3.32
Michiyo Killeen
published 3.5
3.31
Mariles Valencia
published 4
3.27
Bea Vega
published 3.5
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.

Chigusa Okubo + Emi Kanayama251653% games−0.5% vs expected
Julie Wunderly + Junko Toda8456% games−0.7% vs expected
Bea Vega + Mariles Valencia181750% games−1.5% vs expected
Haruko Vajda + Julie Wunderly5746% gamesnot enough data
Haruko Vajda + Junko Toda8457% gamesnot enough data
Joan Yngson + Emi Kanayama134 matchesnot enough data
Chigusa Okubo + Mariles Valencia044 matchesnot enough data
Chigusa Okubo + Junko Toda213 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.

4.5
Junko Toda
246W–88L career · no lines in 2022
25%75%<1%
4.09
4
Chigusa Okubo
55W–55L career · no lines in 2022
not enough data
4
Emi Kanayama
85W–63L career · no lines in 2022
8%92%1%
3.69
4
Jennifer Kries
102W–95L career · no lines in 2022
22%78%<1%
3.60
4
Julie Wunderly
60W–58L career · no lines in 2022
23%77%<1%
3.60
4
Veronica Ruffo
135W–157L career · no lines in 2022
26%74%<1%
3.58
Joan Yngson
4W–6L career · no lines in 2022
31%69%<1%
3.57
4
Haruko Vajda
165W–125L career · no lines in 2022
49%51%<1%
3.50
3.5
Michiyo Killeen
13W–20L career · no lines in 2022
1%91%9%
3.32
4
Mariles Valencia
48W–80L career · no lines in 2022
92%8%<1%
3.31
3.5
Bea Vega
154W–161L career · no lines in 2022
2%94%4%
3.27

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.