Teams

SDNC 3.5WE RPTC/ Chen

2022 Adult 18 & Over Spring - SDNC WE Women · SDNC - Women- WE 3.5

10 players · average NTRP 3.60 / 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 →
Schedule7 played
2022-06-26vs SDNC 3.5WE Winner's TC/ PretiSplit 11
L#1 DoublesGrace Reyno / Denise Wilson vs Crista Hubbard / HONG ZEMAN0-6, 6-1, 0-1
W#2 DoublesJunli Feng / Tomoko Hoffman vs Heidi Ulrich / Gracie Jones5-7, 6-2, 1-0
L#1 DoublesAnn Hou / Grace Reyno vs Lindsey Harp / Leslie Mereminsky6-7, 4-6
L#2 DoublesLiz Perkins / Junli Feng vs Hillary Emery / Alison Pasiut3-6, 2-6
2022-06-12vs SDNC 3.5WE Kit Carson Park/ NelsonLost 01
L#1 DoublesJunli Feng / Tomoko Hoffman vs Charis Ioannides / Emily Adamiec3-6, 5-7
2022-05-15Won 10
W#1 SinglesKalpana Chalasani vs Jill Narlock6-3, 6-3
2022-04-24vs SDNC 3.5WE Winner's TC/ PretiLost 02
L#1 DoublesGrace Reyno / Ann Hou vs Crista Hubbard / HONG ZEMAN4-6, 4-6
L#1 SinglesKalpana Chalasani vs Elena Gilmor4-6, 2-6
W#1 SinglesTomoko Hoffman vs Lori Kartsub2-6, 6-3, 1-0
W#1 SinglesKalpana Chalasani vs Leslie Mereminsky6-0, 6-4
A tie can be incomplete. Tell us if someone is missing.
i
Grouped by tie — one fixture, several lines. A line shows only when a player on it is someone we have indexed, so an early-season tie for a newly-added team can look short. This also means the line count here will not match the header, which counts individual player appearances.

Flight standings for SDNC - Women- WE 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 3.33 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.

3.79
Ann Hou
published 4
3.58
Kalpana Chalasani
usually #1 Singles 100% · published 3.5
3.46
Tomoko Hoffman
usually #1 Singles 33%, also #1 Doubles 33% · published 3.5
3.38
Junli Feng
usually #2 Doubles 67%, also #1 Doubles 33% · published 3.5
3.34
Ping Chen
published
3.27
Grace Reyno
usually #1 Doubles 80%, also #2 Doubles 20% · published 3.5
3.24
Vicki Pineda
published
3.17
Tho Mora
published
3.10
Lisa Ishihara
published
2.98
Liz Perkins
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.

Junli Feng + Ping Chen303 matchesnot enough data
Vicki Pineda + Tho Mora123 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
Ann Hou
2W–6L career · no lines in 2022
1%93%5%
3.79
3.5
Kalpana Chalasani
88W–31L career · 3 lines in 2022
<1%27%73%
3.58
3.5
Tomoko Hoffman
89W–99L career · 3 lines in 2022
<1%62%38%
3.46
3.5
Junli Feng
90W–63L career · 3 lines in 2022
<1%83%17%
3.38
Ping Chen
14W–11L career · no lines in 2022
<1%88%12%
3.34
3.5
Grace Reyno
44W–35L career · 5 lines in 2022
2%94%4%
3.27
Vicki Pineda
1W–4L career · no lines in 2022
3%94%2%
3.24
Tho Mora
4W–4L career · no lines in 2022
10%90%1%
3.17
Lisa Ishihara
1W–2L career · no lines in 2022
21%79%<1%
3.10
Liz Perkins
16W–10L career · no lines in 2022
<1%55%45%
2.98

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.